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For industrial product design, it is very important to take into account assembly/disassembly and maintenance operations during the conceptual and prototype design stage. For these operations or other similar operations in a constrained environment, trajectory planning is always a critical and difficult issue for evaluating the design or for the users' convenience. In this paper, a customer-oriented approach is proposed to partially solve ergonomic issues encountered during the design stage of a constrained environment. A single objective optimization based method is taken from the literature to generate the trajectory in a constrained environment automatically. A motion capture based method assists to guide the trajectory planning interactively if a local minimum is encountered within the single objective optimization. At last, a multi-objective evaluation method is proposed to evaluate the operations generated by the algorithm
Using virtual human for an interactive customer-oriented constrained environment design
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In this article we address the problem of catching objects that move at a relatively large distance from the robot, of the order of tens of times the size of the robot itself. To this purpose, we adopt casting manipulation and visual-based feedback control. Casting manipulation is a technique to deploy a robotic end-effector far from the robot's base, by throwing the end-effector and controlling its ballistic flight using forces transmitted through a light tether connected to the end-effector itself. The tether cable can then be used to retrieve the end- effector to exert forces on the robot's environment. In previous work, planar casting manipulation was demon- strated to aptly catch static objects placed at a distant, known position, thus proving it suitable for applications such as sample acquisition and return, rescue, etc. In this paper we propose an extension of the idea to controlling the position of the end- effector to reach moving targets in 3D. The goal is achieved by an innovative design of the casting mechanism, and by closing a real-time control loop on casting manipulation using visual feedback of moving targets. To achieve this result, simplified yet accurate models of the system suitable for real-time computation are developed, along with a suitable visual feedback scheme for the flight phase. Effectiveness of the visual feedback controller is demonstrated through experiments with a 2D casting robot.
Casting Robotic End-effectors To Reach Faraway Moving Objects
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In this paper, we propose a decentralized coordina- tion algorithm for safe and efficient management of a group of mobile robots following predefined paths in a dynamic industrial environment. The proposed algorithm is based on a shared resources protocol and a replanning strategy. It is proved to guarantee ordered traffic flows avoiding collisions, deadlocks (stall situations) and livelock (agents move without reaching final destinations). Mutual access to resources has been proved for the proposed approach while condition on the maximum number of AGVs is given to ensure the absence of deadlocks during system evolutions. Finally conditions to verify a local livelocks will also be proposed. In consistency with the model of distributed robotic systems (DRS), no centralized mechanism, synchronized clock, shared memory or ground support is needed. A local inter-robot communication, based on sign-boards, is considered among a small number of spatially adjacent robotic units.
Distributed Collision-free Protocol for AGVs in Industrial Environments
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In this paper we introduce a novel consensus mech- anism where agents of a network are able to share logical values, or Booleans, representing their local opinions on e.g. the presence of an intruder or of a fire within an indoor environment. We first formulate the logical consensus problem, and then we review relevant results in the literature on cellular automata and convergence of finite-state iteration maps. Under suitable joint conditions on the visibility of agents and their communication capability, we provide an algorithm for generating a logical linear consensus system that is globally stable. The solution is optimal in terms of the number of messages to be exchanged and the time needed to reach a consensus. Moreover, to cope with possible sensor failure, we propose a second design approach that produces robust logical nonlinear consensus systems tolerating a given maximum number of faults. Finally, we show applicability of the agreement mechanism to a case study consisting of a distributed Intrusion Detection System (IDS).
Logical Consensus for Distributed and Robust Intrusion Detection
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This paper addresses the problem of detecting possible intruders in a group of autonomous robots, which coexist in a shared environment and interact with each other according to a set of "social behaviors", or common rules. Such rules specify what actions each robot is allowed to perform in the pursuit of its individual goals: rules are distributed, i.e. they can evaluated based only on the state of the individual robot, and on information that can be sensed directly or through communication with immediate neighbors. We consider intruders as robots which misbehave, i.e. do not follow the rules, because of either spontaneous failures or malicious reprogramming. Our goal is to detect intruders by observing the congruence of their behavior with the social rules as applied to the current state of the overall system. Moreover, in accordance with the fully distributed nature of the problem, the detection itself must be peformed by individual robots, based only on local information. The paper introduces a formalism that allows to model uniformly a large variety of possible robot societies. The main contribution consists in the proposal of an Intrusion Detection System, i.e. a protocol that, under suitabkle conditions, allows individual robots to detect possible misbehaving robots in their vicinity, and trigger possible further actions to secure the society. It is worth noting that the generality of the protocol formalism makes so that local monitors can be automatically generated once the cooperation rules and the robot dynamics are specified. The effectiveness of the proposed technique is shown through application to examples of automated robotic systems.
Distributed Intrusion Detection for the Security of Societies of Robots
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This paper focuses on the convergence of infor- mation in distributed systems of agents communicating over a network. The information on which the convergence is sought is not represented by real numbers, rather by sets of real numbers, whose possible dynamics are given by the class of so-called Boolean maps, involving only unions, intersections, and complements of sets. Based on a notion of contractivity, a necessary and sufficient condition ensuring the global and local convergence toward an equilibrium point is presented. In particular the analysis of global convergence recovers results already obtained by the authors, but the more general approach used in this paper allows analogue results to be found to characterize the local convergence.
Distributed Consensus on Set-valued Information
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This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a key capability in order to make robots suitable to perform high-level tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings.
Evaluation of Three Vision Based Object Perception Methods for a Mobile Robot
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We present a complete characterization of shortest paths to a goal position for a vehicle with unicycle kinematics and a limited range sensor, constantly keeping a given landmark in sight. Previous work on this subject studied the optimal paths in case of a frontal, symmetrically limited Field--Of--View (FOV). In this paper we provide a generalization to the case of arbitrary FOVs, including the case that the direction of motion is not an axis of symmetry for the FOV, and even that it is not contained in the FOV. The provided solution is of particular relevance to applications using side-scanning, such as e.g. in underwater sonar-based surveying and navigation.
Optimal Synthesis for Nonholonomic Vehicles With Constrained Side Sensors
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We consider the eigenvalue problem for the case where the input matrix is symmetric and its entries perturb in some given intervals. We present a characterization of some of the exact boundary points, which allows us to introduce an inner approximation algorithm, that in many case estimates exact bounds. To our knowledge, this is the first algorithm that is able to guaran- tee exactness. We illustrate our approach by several examples and numerical experiments.
Characterizing and approximating eigenvalue sets of symmetric interval matrices
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Current progresses in home automation and service robotic environment have highlighted the need to develop interoperability mechanisms that allow a standard communication between the two systems. During the development of the DHCompliant protocol, the problem of locating mobile devices in an indoor environment has been investigated. The communication of the device with the location service has been carried out to study the time delay that web services offer in front of the sockets. The importance of obtaining data from real-time location systems portends that a basic tool for interoperability, such as web services, can be ineffective in this scenario because of the delays added in the invocation of services. This paper is focused on introducing a web service to resolve a coordinates request without any significant delay in comparison with the sockets.
Visual Localisation of Mobile Devices in an Indoor Environment under Network Delay Conditions
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In this research report details of design of a miniature wheel arrangement are presented. This miniature wheel arrangement is essentially a direction control mechanism intended for use on a mobile robot platform or base. The design is a specific one employing a stepper motor as actuator and as described can only be used on a certain type of wheeled robots. However, as a basic steering control element, more than one of these miniature wheel arrangements can be grouped together to implement more elaborate and intelligent direction control schemes on varying configurations of wheeled mobile robot platforms.
Designing a Miniature Wheel Arrangement for Mobile Robot Platforms
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The paper presents a methodology to enhance the stiffness analysis of serial and parallel manipulators with passive joints. It directly takes into account the loading influence on the manipulator configuration and, consequently, on its Jacobians and Hessians. The main contributions of this paper are the introduction of a non-linear stiffness model for the manipulators with passive joints, a relevant numerical technique for its linearization and computing of the Cartesian stiffness matrix which allows rank-deficiency. Within the developed technique, the manipulator elements are presented as pseudo-rigid bodies separated by multidimensional virtual springs and perfect passive joints. Simulation examples are presented that deal with parallel manipulators of the Ortholide family and demonstrate the ability of the developed methodology to describe non-linear behavior of the manipulator structure such as a sudden change of the elastic instability properties (buckling).
Enhanced stiffness modeling of manipulators with passive joints
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This paper presents a new method, based on a multi-agent system and on a digital mock-up technology, to assess an efficient path planner for a manikin or a robot for access and visibility task taking into account ergonomic constraints or joint and mechanical limits. In order to solve this problem, the human operator is integrated in the process optimization to contribute to a global perception of the environment. This operator cooperates, in real-time, with several automatic local elementary agents. The result of this work validates solutions through the digital mock-up; it can be applied to simulate maintenability and mountability tasks.
A distributed Approach for Access and Visibility Task with a Manikin and a Robot in a Virtual Reality Environment
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This paper presents the development of a new software in order to manage objects, robots and mannequins in using the possibilities given by the haptic feedback of the Phantom desktop devices. The haptic device provides 6 positional degrees of freedom sensing but three degrees force feedback. This software called eM-Virtual Desktop is integrated in the Tecnomatix's solution called eM-Workplace. The eM-Workplace provides powerful solutions for planning and designing of complex assembly facilities, lines and workplaces. In the digital mockup context, the haptic interfaces can be used to reduce the development cycle of products. Three different loops are used to manage the graphic, the collision detection and the haptic feedback according to theirs own frequencies. The developed software is currently tested in industrial context by a European automotive constructor.
Haptic devices and objects, robots and mannequin simulation in a CAD-CAM software: eM-Virtual Desktop
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With the increasing of computer capabilities, Computer aided ergonomics (CAE) offers new possibilities to integrate conventional ergonomic knowledge and to develop new methods into the work design process. As mentioned in [1], different approaches have been developed to enhance the efficiency of the ergonomic evaluation. Ergonomic expert systems, ergonomic oriented information systems, numerical models of human, etc. have been implemented in numerical ergonomic software. Until now, there are ergonomic software tools available, such as Jack, Ergoman, Delmia Human, 3DSSPP, and Santos, etc. [2-4]. The main functions of these tools are posture analysis and posture prediction. In the visualization part, Jack and 3DSSPP produce results to visualize virtual human tasks in 3-dimensional, but without realistic physical properties. Nowadays, with the development of computer technology, the simulation of physical world is paid more attention. Physical engines [5] are used more and more in computer game (CG) field. The advantage of physical engine is the nature physical world environment simulation. The purpose of our research is to use the CG technology to create a virtual environment with physical properties for ergonomic analysis of virtual human.
A framework of motion capture system based human behaviours simulation for ergonomic analysis
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Parallel robots admit generally several solutions to the direct kinematics problem. The aspects are associated with the maximal singularity free domains without any singular configurations. Inside these regions, some trajectories are possible between two solutions of the direct kinematic problem without meeting any type of singularity: non-singular assembly mode trajectories. An established condition for such trajectories is to have cusp points inside the joint space that must be encircled. This paper presents an approach based on the notion of uniqueness domains to explain this behaviour.
Uniqueness domains and non singular assembly mode changing trajectories
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In ergonomics and biomechanics, muscle fatigue models based on maximum endurance time (MET) models are often used to integrate fatigue effect into ergonomic and biomechanical application. However, due to the empirical principle of those MET models, the disadvantages of this method are: 1) the MET models cannot reveal the muscle physiology background very well; 2) there is no general formation for those MET models to predict MET. In this paper, a theoretical MET model is extended from a simple muscle fatigue model with consideration of the external load and maximum voluntary contraction in passive static exertion cases. The universal availability of the extended MET model is analyzed in comparison to 24 existing empirical MET models. Using mathematical regression method, 21 of the 24 MET models have intraclass correlations over 0.9, which means the extended MET model could replace the existing MET models in a general and computationally efficient way. In addition, an important parameter, fatigability (or fatigue resistance) of different muscle groups, could be calculated via the mathematical regression approach. Its mean value and its standard deviation are useful for predicting MET values of a given population during static operations. The possible reasons influencing the fatigue resistance were classified and discussed, and it is still a very challenging work to find out the quantitative relationship between the fatigue resistance and the influencing factors.
A novel approach for determining fatigue resistances of different muscle groups in static cases
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This paper presents our work on relationship of evaluation results between virtual environment (VE) and realistic environment (RE) for assembling tasks. Evaluation results consist of subjective results (BPD and RPE) and objective results (posture and physical performance). Same tasks were performed with same experimental configurations and evaluation results were measured in RE and VE respectively. Then these evaluation results were compared. Slight difference of posture between VE and RE was found but not great difference of effect on people according to conventional ergonomics posture assessment method. Correlation of BPD and performance results between VE and RE are found by linear regression method. Moreover, results of BPD, physical performance, and RPE in VE are higher than that in RE with significant difference. Furthermore, these results indicates that subjects feel more discomfort and fatigue in VE than RE because of additional effort required in VE.
Can virtual reality predict body part discomfort and performance of people in realistic world for assembling tasks?
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The design of a novel prismatic drive is reported in this paper. This transmission is based on Slide-o-Cam, a cam mechanism with multiple rollers mounted on a common translating follower. The design of Slide-o-Cam was reported elsewhere. This drive thus provides pure-rolling motion, thereby reducing the friction of rack-and-pinions and linear drives. Such properties can be used to design new transmissions for parallel-kinematics machines. In this paper, this transmission is intended to replace the ball-screws in Orthoglide, a three-dof parallel robot intended for machining applications.
The Design of a Novel Prismatic Drive for a Three-DOF Parallel-Kinematics Machine
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Planning trajectories for nonholonomic systems is difficult and computationally expensive. When facing unexpected events, it may therefore be preferable to deform in some way the initially planned trajectory rather than to re-plan entirely a new one. We suggest here a method based on affine transformations to make such deformations. This method is exact and fast: the deformations and the resulting trajectories can be computed algebraically, in one step, and without any trajectory re-integration. To demonstrate the possibilities offered by this new method, we use it to derive position and orientation correction algorithms for the general class of planar wheeled robots and for a tridimensional underwater vehicle. These algorithms allow in turn achieving more complex applications, including obstacle avoidance, feedback control or gap filling for sampling-based kinodynamic planners.
Affine trajectory correction for nonholonomic mobile robots
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According to the American Heritage Dictionary [1],Robotics is the science or study of the technology associated with the design, fabrication, theory, and application of Robots. The term Hoverbot is also often used to refer to sophisticated mechanical devices that are remotely controlled by human beings even though these devices are not autonomous. This paper describes a remotely controlled hoverbot by installing a transmitter and receiver on both sides that is the control computer (PC) and the hoverbot respectively. Data is transmitted as signal or instruction via a infrastructure network which is converted into a command for the hoverbot that operates at a remote site.
An Unmanned Aerial Vehicle as Human-Assistant Robotics System
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During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.
Sampling-based Algorithms for Optimal Motion Planning
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The ability to place objects in the environment is an important skill for a personal robot. An object should not only be placed stably, but should also be placed in its preferred location/orientation. For instance, a plate is preferred to be inserted vertically into the slot of a dish-rack as compared to be placed horizontally in it. Unstructured environments such as homes have a large variety of object types as well as of placing areas. Therefore our algorithms should be able to handle placing new object types and new placing areas. These reasons make placing a challenging manipulation task. In this work, we propose a supervised learning algorithm for finding good placements given the point-clouds of the object and the placing area. It learns to combine the features that capture support, stability and preferred placements using a shared sparsity structure in the parameters. Even when neither the object nor the placing area is seen previously in the training set, our algorithm predicts good placements. In extensive experiments, our method enables the robot to stably place several new objects in several new placing areas with 98% success-rate; and it placed the objects in their preferred placements in 92% of the cases.
Learning to Place New Objects
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Cusps and nodes on plane sections of the singularity locus in the joint space of parallel manipulators play an important role in nonsingular assembly-mode changing motions. This paper analyses in detail such points, both in the joint space and in the workspace. It is shown that a cusp (resp. a node) defines a point of tangency (resp. a crossing point) in the workspace between the singular curves and the curves associated with the so-called characteristics surfaces. The study is conducted on a planar 3-RPR manipulator for illustrative purposes.
A study of the singularity locus in the joint space of planar parallel manipulators: special focus on cusps and nodes
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Inexpensive RGB-D cameras that give an RGB image together with depth data have become widely available. We use this data to build 3D point clouds of a full scene. In this paper, we address the task of labeling objects in this 3D point cloud of a complete indoor scene such as an office. We propose a graphical model that captures various features and contextual relations, including the local visual appearance and shape cues, object co-occurrence relationships and geometric relationships. With a large number of object classes and relations, the model's parsimony becomes important and we address that by using multiple types of edge potentials. The model admits efficient approximate inference, and we train it using a maximum-margin learning approach. In our experiments over a total of 52 3D scenes of homes and offices (composed from about 550 views, having 2495 segments labeled with 27 object classes), we get a performance of 84.06% in labeling 17 object classes for offices, and 73.38% in labeling 17 object classes for home scenes. Finally, we applied these algorithms successfully on a mobile robot for the task of finding an object in a large cluttered room.
Labeling 3D scenes for Personal Assistant Robots
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In this paper we present a method for automatically planning optimal paths for a group of robots that satisfy a common high level mission specification. Each robot's motion in the environment is modeled as a weighted transition system. The mission is given as a Linear Temporal Logic formula. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize the maximum time between satisfying instances of the optimizing proposition. Our method is guaranteed to compute an optimal set of robot paths. We utilize a timed automaton representation in order to capture the relative position of the robots in the environment. We then obtain a bisimulation of this timed automaton as a finite transition system that captures the joint behavior of the robots and apply our earlier algorithm for the single robot case to optimize the group motion. We present a simulation of a persistent monitoring task in a road network environment.
Optimal Multi-Robot Path Planning with Temporal Logic Constraints
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The paper focuses on stiffness matrix computation for manipulators with passive joints. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in general case and allow obtaining the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and non-singular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.
Cartesian stiffness matrix of manipulators with passive joints: analytical approach
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We study in this paper a class of 3-RPR manipulators for which the direct kinematic problem (DKP) is split into a cubic problem followed by a quadratic one. These manipulators are geometrically characterized by the fact that the moving triangle is the image of the base triangle by an indirect isometry. We introduce a specific coordinate system adapted to this geometric feature and which is also well adapted to the splitting of the DKP. This allows us to obtain easily precise descriptions of the singularities and of the cusp edges. These latter second order singularities are important for nonsingular assembly mode changing. We show how to sort assembly modes and use this sorting for motion planning in the joint space.
Singular surfaces and cusps in symmetric planar 3-RPR manipulators
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A novel sensory substitution technique is presented. Kinesthetic and cutaneous force feedback are substituted by cutaneous feedback (CF) only, provided by two wearable devices able to apply forces to the index finger and the thumb, while holding a handle during a teleoperation task. The force pattern, fed back to the user while using the cutaneous devices, is similar, in terms of intensity and area of application, to the cutaneous force pattern applied to the finger pad while interacting with a haptic device providing both cutaneous and kinesthetic force feedback. The pattern generated using the cutaneous devices can be thought as a subtraction between the complete haptic feedback (HF) and the kinesthetic part of it. For this reason, we refer to this approach as sensory subtraction instead of sensory substitution. A needle insertion scenario is considered to validate the approach. The haptic device is connected to a virtual environment simulating a needle insertion task. Experiments show that the perception of inserting a needle using the cutaneous-only force feedback is nearly indistinguishable from the one felt by the user while using both cutaneous and kinesthetic feedback. As most of the sensory substitution approaches, the proposed sensory subtraction technique also has the advantage of not suffering from stability issues of teleoperation systems due, for instance, to communication delays. Moreover, experiments show that the sensory subtraction technique outperforms sensory substitution with more conventional visual feedback (VF).
Cutaneous Force Feedback as a Sensory Subtraction Technique in Haptics
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In this paper we present the study of the mathematical model of a real life joint used in an underwater robotic fish. Fluid-structure interaction is utterly simplified and the motion of the joint is approximated by D\"uffing's equation. We compare the quality of analytical harmonic solutions previously reported, with the input-output relation obtained via truncated Volterra series expansion. Comparisons show a trade-off between accuracy and flexibility of the methods. The methods are discussed in detail in order to facilitate reproduction of our results. The approach presented herein can be used to verify results in nonlinear resonance applications and in the design of bio-inspired compliant robots that exploit passive properties of their dynamics. We focus on the potential use of this type of joint for energy extraction from environmental sources, in this case a K\'arm\'an vortex street shed by an obstacle in a flow. Open challenges and questions are mentioned throughout the document.
Modeling and frequency domain analysis of nonlinear compliant joints for a passive dynamic swimmer
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Reasons for Performing Study: Equine gait analysis has focused on 2D analysis in the sagittal plane, while descriptions of 3D kinetics and ground reaction force could provide more information on the Equine gait analysis. Hypothesis or Objectives: The aim of this study was to characterize the 3D torques and powers of the forelimb joints at trotting. Methods: Eight sound horses were used in the study. A full 3D torque and power for elbow, carpus, fetlock, pastern and coffin joints of right forelimb in horses at trot were obtained by calculating the inverse kinetics of simplified link segmental model. Results: Over two third of energy (70%) generated by all joints come from stance phase, and most of energy generated was by elbow joint both in stance (77%) and sway (88%) phases. Energy absorbed by all joints during stance (40%) and sway (60%) phases respectively is not a big difference. During stance phase, all most two third of energy (65%) absorbed was by fetlock joint, while over two third of energy (74%) absorbed was by carpus joint during sway phase. Conclusions & Clinical Relevance: This study presents a full 3D kinetic analysis of the relative motion of the humerus, radius, cannon, pastern and coffin segments of the forelimb at the trot. The results could provide for a more sensitive measure for kinetic analysis.
Three-dimensional Torques and Power of Horse Forelimb Joints at Trot
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Summary of results in last project period (1. 10. 2009 - 30. 9. 2010) of SNFS Project "From locomotion to cognition" The research that we have been involved in, and will continue to do, starts from the insight that in order to understand and design intelligent behavior, we must adopt an embodied perspective, i.e. we must take the entire agent, including its shape or morphology, the materials out of which it is built, and its interaction with the environment into account, in addition to the neural control. A lot of our research in the past has been on relatively low-level sensory-motor tasks such as locomotion (e.g. walking, running, jumping), navigation, and grasping. While this research is of interest in itself, in the context of artificial intelligence and cognitive science, this leads to the question of what these kinds of tasks have to do with higher levels of cognition, or to put it more provocatively, "What does walking have to do with thinking?" This question is of course reminiscent of the notorious "symbol grounding problem". In contrast to most of the research on symbol grounding, we propose to exploit the dynamic interaction between the embodied agent and the environment as the basis for grounding. We use the term "morphological computation" to designate the fact that some of the control or computation can be taken over by the dynamic interaction derived from morphological properties (e.g. the passive forward swing of the leg in walking, the spring-like properties of the muscles, and the weight distribution). By taking morphological computation into account, an agent will be able to achieve not only faster, more robust, and more energy-efficient behavior, but also more situated exploration by the agent for the comprehensive understanding of the environment.
SNF Project Locomotion: Final report 2009-2010
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Summary of results (project period 1. 10. 2008 - 30. 9. 2009) of SNFS Project "From locomotion to cognition" The research that we have been involved in, and will continue to do, starts from the insight that in order to understand and design intelligent behavior, we must adopt an embodied perspective, i.e. we must take the entire agent, including its shape or morphology, the materials out of which it is built, and its interaction with the environment into account, in addition to the neural control. A lot of our research in the past has been on relatively low-level sensory-motor tasks such as locomotion (e.g. walking, running, jumping), navigation, and grasping. While this research is of interest in itself, in the context of artificial intelligence and cognitive science, this leads to the question of what these kinds of tasks have to do with higher levels of cognition, or to put it more provocatively, "What does walking have to do with thinking?" This question is of course reminiscent of the notorious "symbol grounding problem". In contrast to most of the research on symbol grounding, we propose to exploit the dynamic interaction between the embodied agent and the environment as the basis for grounding. We use the term "morphological computation" to designate the fact that some of the control or computation can be taken over by the dynamic interaction derived from morphological properties (e.g. the passive forward swing of the leg in walking, the spring-like properties of the muscles, and the weight distribution). By taking morphological computation into account, an agent will be able to achieve not only faster, more robust, and more energy-efficient behavior, but also more situated exploration by the agent for the comprehensive understanding of the environment.
SNF Project Locomotion: Progress report 2008-2009
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In this paper, we report the results from the analysis of a numerical model used for the design of a magnetic linear actuator with applications to fin-based locomotion. Most of the current robotic fish generate bending motion using rotary motors which implies at least one mechanical conversion of the motion. We seek a solution that directly bends the fin and, at the same time, is able to exploit the magneto-mechanical properties of the fin material. This strong fin-actuator coupling blends the actuator and the body of the robot, allowing cross optimization of the system's elements. We study a simplified model of an elastic element, a spring-mass system representing a flexible fin, subjected to nonlinear forcing, emulating magnetic interaction. The dynamics of the system is studied under unforced and periodic forcing conditions. The analysis is focused on the limit cycles present in the system, which allows the periodic bending of the fin and the generation of thrust. The frequency, maximum amplitude and center of the periodic orbits (offset of the bending) depend directly on the stiffness of the fin and the intensity of the forcing; we use this dependency to sketch a simple parameter controller. Although the model is strongly simplified, it provides means to estimate first values of the parameters for this kind of actuator and it is useful to evaluate the feasibility of minimal actuation control of such systems.
Magneto-mechanical actuation model for fin-based locomotion
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A simple sample-based planning method is presented which approximates connected regions of free space with volumes in Configuration space instead of points. The algorithm produces very sparse trees compared to point-based planning approaches, yet it maintains probabilistic completeness guarantees. The planner is shown to improve performance on a variety of planning problems, by focusing sampling on more challenging regions of a planning problem, including collision boundary areas such as narrow passages.
Sample-Based Planning with Volumes in Configuration Space
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In this work we consider development of IR-based communication and perception mechanisms for real microrobotic systems. It is demonstrated that a specific combination of hardware and software elements provides capabilities for navigation, objects recognition, directional and unidirectional communication. We discuss open issues and their resolution based on the experiments in the swarm of microrobots "Jasmine".
IR-based Communication and Perception in Microrobotic Swarms
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Micro- and molecular-robotic systems act as large-scale swarms. Capabilities of sensing, communication and information processing are very limited on these scales. This short position paper describes a swarm-based minimalistic approach, which can be applied for coordinating collective behavior in such systems.
New Principles of Coordination in Large-scale Micro- and Molecular-Robotic Groups
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In this work we consider three different cases of robot-robot interactions and resulting global information transfer in robot swarms. These mechanisms define cooperative properties of the system and can be used for designing collective behavior. These three cases are demonstrated and discussed based on experiments in a swarm of microrobots "Jasmine".
Three Cases of Connectivity and Global Information Transfer in Robot Swarms
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Consider a team of agents in the plane searching for and visiting target points that appear in a bounded environment according to a stochastic renewal process with a known absolutely continuous spatial distribution. Agents must detect targets with limited-range onboard sensors. It is desired to minimize the expected waiting time between the appearance of a target point, and the instant it is visited. When the sensing radius is small, the system time is dominated by time spent searching, and it is shown that the optimal policy requires the agents to search a region at a relative frequency proportional to the square root of its renewal rate. On the other hand, when targets appear frequently, the system time is dominated by time spent servicing known targets, and it is shown that the optimal policy requires the agents to service a region at a relative frequency proportional to the cube root of its renewal rate. Furthermore, the presented algorithms in this case recover the optimal performance achieved by agents with full information of the environment. Simulation results verify the theoretical performance of the algorithms.
Optimal Foraging of Renewable Resources
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This work is devoted to communication approaches, which spread information in robot swarms. These mechanisms are useful for large-scale systems and also for such cases when a limited communication equipment does not allow routing of information packages. We focus on two approaches such as virtual fields and epidemic algorithms, discuss several aspects of hardware implementation and demonstrate experiments performed with microrobots "Jasmine".
Diffusion of Information in Robot Swarms
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Performing rescuing and surveillance operations with autonomous ground and aerial vehicles become more and more apparent task. Involving unmanned robot systems allows making these operations more efficient, safe and reliable especially in hazardous areas. This work is devoted to the development of a cost-efficient micro aerial vehicle in a quadrocopter shape for developmental purposes within indoor scenarios. It has been constructed with off-the-shelf components available for mini helicopters. Additional sensors and electronics are incorporated into this aerial vehicle to stabilize its flight behavior and to provide a capability of an autonomous navigation in a partially unstructured indoor environment.
Development of a Cost-efficient Autonomous MAV for an Unstructured Indoor Environment
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Cooperation and competition among stand-alone swarm agents increase collective fitness of the whole system. A principally new kind of collective systems is demonstrated by some bacteria and fungi, when they build symbiotic organisms. Symbiotic life forms emerge new functional and self-developmental capabilities, which allow better survival of swarm agents in different environments. In this paper we consider energy foraging scenario for two robotic species, swarm robots and symbiotic robot organism. It is indicated that aggregation of microrobots into a robot organism can provide better functional fitness for the whole group. A prototype of microrobots capable of autonomous aggregation and disaggregation are shown.
Collective Energy Foraging of Robot Swarms and Robot Organisms
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This paper present new approach in robust indirect rotor field oriented (IRFOC) induction motor (IM) control. The introduction of new exponential reaching law (ERL) based sliding mode control (SMC) improve significantly the performances compared to the conventional SMC which are well known susceptible to the annoying chattering phenomenon, so, the elimination of the chattering is achieved while simplicity and high performance speed and position tracking are maintained. Simulation results are given to discuss the performances of the proposed control method.
High Performance Controllers for Speed and Position Induction Motor Drive using New Reaching Law
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Creation of devices and mechanisms which help people has a long history. Their inventors always targeted practical goals such as irrigation, harvesting, devices for construction sites, measurement, and, last but not least, military tasks for different mechanical and later mechatronic systems. Development of such assisting mechanisms counts back to Greek engineering, came through Middle Ages and led finally in XIX and XX centuries to autonomous devices, which we call today "Robots". This chapter provides overview of several robotic technologies, introduces bio-/chemo- hybrid and collective systems and discuss their applications in service areas.
Robot Companions: Technology for Humans
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Awareness and self-awareness are two different notions related to knowing the environment and itself. In a general context, the mechanism of self-awareness belongs to a class of co-called "self-issues" (self-* or self-star): self-adaptation, self-repairing, self-replication, self-development or self-recovery. The self-* issues are connected in many ways to adaptability and evolvability, to the emergence of behavior and to the controllability of long-term developmental processes. Self-* are either natural properties of several systems, such as self-assembling of molecular networks, or may emerge as a result of homeostatic regulation. Different computational processes, leading to a global optimization, increasing scalability and reliability of collective systems, create such a homeostatic regulation. Moreover, conditions of ecological survival, imposed on such systems, lead to a discrimination between "self" and "non-self" as well as to the emergence of different self-phenomena. There are many profound challenges, such as understanding these mechanisms, or long-term predictability, which have a considerable impact on research in the area of artificial intelligence and intelligent systems.
Awareness and Self-Awareness for Multi-Robot Organisms
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The six axis robots are widely used in automotive industry for their good repeatability (as defined in the ISO92983) (painting, welding, mastic deposition, handling etc.). In the aerospace industry, robot starts to be used for complex applications such as drilling, riveting, fiber placement, NDT, etc. Given the positioning performance of serial robots, precision applications require usually external measurement device with complexes calibration procedure in order to reach the precision needed. New applications in the machining field of composite material (aerospace, naval, or wind turbine for example) intend to use off line programming of serial robot without the use of calibration or external measurement device. For those applications, the position, orientation and path trajectory precision of the tool center point of the robot are needed to generate the machining operation. This article presents the different conditions that currently limit the development of robots in robotic machining applications. We analyze the dynamical behavior of a robot KUKA KR240-2 (located at the University of Bordeaux 1) equipped with a HSM Spindle (42000 rpm, 18kW). This analysis is done in three stages. The first step is determining the self-excited frequencies of the robot structure for three different configurations of work. The second phase aims to analyze the dynamical vibration of the structure as the spindle is activated without cutting. The third stage consists of vibration analysis during a milling operation.
Dynamic behavior analysis for a six axis industrial machining robot
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Attempts to install a rotating tool at the end of a robot arm poly-articulated date back twenty years, but these robots were not designed for that. Indeed, two essential features are necessary for machining: high rigidity and precision in a given workspace. The experimental results presented are the dynamic identification of a poly-articulated robot equipped with an integrated spindle. This study aims to highlight the influence of the geometric configuration of the robot arm on the overall stiffness of the system. The spindle is taken into account as an additional weight on board but also as a dynamical excitation for the robot KUKA KR_240_2. Study of the robotic machining vibrations shows the suitable directions of movement in milling process
Experimental Characterization of Robot Arm Rigidity in Order to Be Used in Machining Operation
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This article presents a new open-source C++ implementation to solve the SLAM problem, which is focused on genericity, versatility and high execution speed. It is based on an original object oriented architecture, that allows the combination of numerous sensors and landmark types, and the integration of various approaches proposed in the literature. The system capacities are illustrated by the presentation of an inertial/vision SLAM approach, for which several improvements over existing methods have been introduced, and that copes with very high dynamic motions. Results with a hand-held camera are presented.
RT-SLAM: A Generic and Real-Time Visual SLAM Implementation
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In this paper we present a method for automatically planning robust optimal paths for a group of robots that satisfy a common high level mission specification. Each robot's motion in the environment is modeled as a weighted transition system, and the mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied by the regions of the environment. In addition, an optimizing proposition must repeatedly be satisfied. The goal is to minimize the maximum time between satisfying instances of the optimizing proposition while ensuring that the LTL formula is satisfied even with uncertainty in the robots' traveling times. We characterize a class of LTL formulas that are robust to robot timing errors, for which we generate optimal paths if no timing errors are present, and we present bounds on the deviation from the optimal values in the presence of errors. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.
Robust Multi-Robot Optimal Path Planning with Temporal Logic Constraints
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Placing is a necessary skill for a personal robot to have in order to perform tasks such as arranging objects in a disorganized room. The object placements should not only be stable but also be in their semantically preferred placing areas and orientations. This is challenging because an environment can have a large variety of objects and placing areas that may not have been seen by the robot before. In this paper, we propose a learning approach for placing multiple objects in different placing areas in a scene. Given point-clouds of the objects and the scene, we design appropriate features and use a graphical model to encode various properties, such as the stacking of objects, stability, object-area relationship and common placing constraints. The inference in our model is an integer linear program, which we solve efficiently via an LP relaxation. We extensively evaluate our approach on 98 objects from 16 categories being placed into 40 areas. Our robotic experiments show a success rate of 98% in placing known objects and 82% in placing new objects stably. We use our method on our robots for performing tasks such as loading several dish-racks, a bookshelf and a fridge with multiple items.
Learning to Place New Objects in a Scene
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This paper develops an algorithm that guides a multi-robot system in an unknown environment in search of fixed targets. The area to be scanned contains an unknown number of convex obstacles of unknown size and shape. The algorithm covers the entire free space in a sweeping fashion and as such relies on the use of robot formations. The geometry of the robot group is a lateral line formation, which is allowed to split and rejoin when passing obstacles. It is our main goal to exploit this formation structure in order to reduce robot resources to a minimum. Each robot has a limited and finite amount of memory available. No information of the topography is recorded. Communication between two robots is only possible up to a maximum inter-robot distance, and if the line-of-sight between both robots is not obstructed. Broadcasting capabilities and indirect communication are not allowed. Supervisory control is prohibited. The number of robots equipped with GPS is kept as small as possible. Applications of the algorithm are mine field clearance, search-and-rescue missions, and intercept missions. Simulations are included and made available on the internet, demonstrating the flexibility of the algorithm.
Multi-robot coverage to locate fixed targets using formation structures
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The paper focuses on stiffness matrix computation for manipulators with passive joints, compliant actuators and flexible links. It proposes both explicit analytical expressions and an efficient recursive procedure that are applicable in the general case and allow obtaining the desired matrix either in analytical or numerical form. Advantages of the developed technique and its ability to produce both singular and non-singular stiffness matrices are illustrated by application examples that deal with stiffness modeling of two Stewart-Gough platforms.
Stiffness matrix of manipulators with passive joints: computational aspects
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Artificial immune systems primarily mimic the adaptive nature of biological immune functions. Their ability to adapt to varying pathogens makes such systems a suitable choice for various robotic applications. Generally, AIS-based robotic applications map local instantaneous sensory information into either an antigen or a co-stimulatory signal, according to the choice of representation schema. Algorithms then use relevant immune functions to output either evolved antibodies or maturity of dendritic cells, in terms of actuation signals. It is observed that researchers, in an attempt to solve the problem in hand, do not try to replicate the biological immunity but select necessary immune functions instead, resulting in an ad-hoc manner these applications are reported. Authors, therefore, present a comprehensive review of immuno-inspired robotic applications in an attempt to categorize them according to underlying immune definitions. Implementation details are tabulated in terms of corresponding mathematical expressions and their representation schema that include binary, real or hybrid data. Limitations of reported applications are also identified in light of modern immunological interpretations. As a result of this study, authors suggest a renewed focus on innate immunity and also emphasize that immunological representations should benefit from robot embodiment and must be extended to include modern trends.
Immuno-inspired robotic applications: a review
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In modern life the road safety has becomes the core issue. One single move of a driver can cause horrifying accident. The main goal of intelligent car system is to make communication with other cars on the road. The system is able to control to speed, direction and the distance between the cars the intelligent car system is able to recognize traffic light and is able to take decision according to it. This paper presents a framework of the intelligent car system. I validate several aspect of our system using simulation.
Intelligent Car System
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We present a simple and natural extension of the multi-robot motion planning problem where the robots are partitioned into groups (colors), such that in each group the robots are interchangeable. Every robot is no longer required to move to a specific target, but rather to some target placement that is assigned to its group. We call this problem k-color multi-robot motion planning and provide a sampling-based algorithm specifically designed for solving it. At the heart of the algorithm is a novel technique where the k-color problem is reduced to several discrete multi-robot motion planning problems. These reductions amplify basic samples into massive collections of free placements and paths for the robots. We demonstrate the performance of the algorithm by an implementation for the case of disc robots and polygonal robots translating in the plane. We show that the algorithm successfully and efficiently copes with a variety of challenging scenarios, involving many robots, while a simplified version of this algorithm, that can be viewed as an extension of a prevalent sampling-based algorithm for the k-color case, fails even on simple scenarios. Interestingly, our algorithm outperforms a well established implementation of PRM for the standard multi-robot problem, in which each robot has a distinct color.
k-Color Multi-Robot Motion Planning
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We consider the synthesis of control policies from temporal logic specifications for robots that interact with multiple dynamic environment agents. Each environment agent is modeled by a Markov chain whereas the robot is modeled by a finite transition system (in the deterministic case) or Markov decision process (in the stochastic case). Existing results in probabilistic verification are adapted to solve the synthesis problem. To partially address the state explosion issue, we propose an incremental approach where only a small subset of environment agents is incorporated in the synthesis procedure initially and more agents are successively added until we hit the constraints on computational resources. Our algorithm runs in an anytime fashion where the probability that the robot satisfies its specification increases as the algorithm progresses.
Incremental Temporal Logic Synthesis of Control Policies for Robots Interacting with Dynamic Agents
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One of the major impacts of climatic changes is due to destroying of forest. Destroying of forest takes place in many ways but the majority of the forest is destroyed due to wild forest fires. In this paper we have presented a path planning algorithm for extinguishing fires which uses Wireless Sensor and Actor Networks (WSANs) for detecting fires. Since most of the works on forest fires are based on Wireless Sensor Networks (WSNs) and a collection of work has been done on coverage, message transmission, deployment of nodes, battery power depletion of sensor nodes in WSNs we focused our work in path planning approach of the Actor to move to the target area where the fire has occurred and extinguish it. An incremental approach is presented in order to determine the successive moves of the Actor to extinguish fire in an environment with and without obstacles. This is done by comparing the moves determined with target location readings obtained using sensors until the Actor reaches the target area to extinguish fires.
Path Planning Algorithm for Extinguishing Forest Fires
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This paper considers onboard control of a small-sized quadrotor using a strapdown embedded optical flow sensor which is conventionally used for desktop mice. The vehicle considered in this paper can carry only few dozen grams of payload, therefore conventional camera-based optical flow methods are not applicable. We present hovering control of the small-sized quadrotor using a single-chip optical flow sensor, implemented on an 8-bit microprocessor without external sensors or communication with a ground control station. Detailed description of all the system components is provided along with evaluation of the accuracy. Experimental results from flight tests are validated with the ground-truth data provided by a high-accuracy reference system.
Onboard Flight Control of a Small Quadrotor Using Single Strapdown Optical Flow Sensor
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We address the problem of estimating a rigid transformation between two point sets, which is a key module for target tracking system using Light Detection And Ranging (LiDAR). A fast implementation of Expectation-maximization (EM) algorithm is presented whose complexity is O(N) with $N$ the number of scan points.
Estimating Rigid Transformation Between Two Range Maps Using Expectation Maximization Algorithm
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Military is one of many industries that is more computer-dependent than ever before, from soldiers with computerized weapons, and tactical wireless devices, to commanders with advanced battle management, command and control systems. Fundamentally, command and control is the process of planning, monitoring, and commanding military personnel, weaponry equipment, and combating vehicles to execute military missions. In fact, command and control systems are revolutionizing as war fighting is changing into cyber, technology, information, and unmanned warfare. As a result, a new design model that supports scalability, reusability, maintainability, survivability, and interoperability is needed to allow commanders, hundreds of miles away from the battlefield, to plan, monitor, evaluate, and control the war events in a dynamic, robust, agile, and reliable manner. This paper proposes a service-oriented architecture for weaponry and battle command and control systems, made out of loosely-coupled and distributed web services. The proposed architecture consists of three elementary tiers: the client tier that corresponds to any computing military equipment; the server tier that corresponds to the web services that deliver the basic functionalities for the client tier; and the middleware tier that corresponds to an enterprise service bus that promotes interoperability between all the interconnected entities. A command and control system was simulated and experimented and it successfully exhibited the desired features of SOA. Future research can improve upon the proposed architecture so much so that it supports encryption for securing the exchange of data between the various communicating entities of the system.
Service-Oriented Architecture for Weaponry and Battle Command and Control Systems in Warfighting
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Currently, industrial sectors are transforming their business processes into e-services and component-based architectures to build flexible, robust, and scalable systems, and reduce integration-related maintenance and development costs. Robotics is yet another promising and fast-growing industry that deals with the creation of machines that operate in an autonomous fashion and serve for various applications including space exploration, weaponry, laboratory research, and manufacturing. It is in space exploration that the most common type of robots is the planetary rover which moves across the surface of a planet and conducts a thorough geological study of the celestial surface. This type of rover system is still ad-hoc in that it incorporates its software into its core hardware making the whole system cohesive, tightly-coupled, more susceptible to shortcomings, less flexible, hard to be scaled and maintained, and impossible to be adapted to other purposes. This paper proposes a service-oriented architecture for space exploration robotic rover systems made out of loosely-coupled and distributed web services. The proposed architecture consists of three elementary tiers: the client tier that corresponds to the actual rover; the server tier that corresponds to the web services; and the middleware tier that corresponds to an Enterprise Service Bus which promotes interoperability between the interconnected entities. The niche of this architecture is that rover's software components are decoupled and isolated from the rover's body and possibly deployed at a distant location. A service-oriented architecture promotes integrate-ability, scalability, reusability, maintainability, and interoperability for client-to-server communication.
Service-Oriented Architecture for Space Exploration Robotic Rover Systems
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As general purpose robots become more capable, pre-programming of all tasks at the factory will become less practical. We would like for non-technical human owners to be able to communicate, through interaction with their robot, the details of a new task; we call this interaction "task communication". During task communication the robot must infer the details of the task from unstructured human signals and it must choose actions that facilitate this inference. In this paper we propose the use of a partially observable Markov decision process (POMDP) for representing the task communication problem; with the unobservable task details and unobservable intentions of the human teacher captured in the state, with all signals from the human represented as observations, and with the cost function chosen to penalize uncertainty. We work through an example representation of task communication as a POMDP, and present results from a user experiment on an interactive virtual robot, compared with a human controlled virtual robot, for a task involving a single object movement and binary approval input from the teacher. The results suggest that the proposed POMDP representation produces robots that are robust to teacher error, that can accurately infer task details, and that are perceived to be intelligent.
Framing Human-Robot Task Communication as a POMDP
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This paper reviews the aspects of the LEGO\textregistered Mindstorms\trademark robotics invention system 2.0 \trademark (RIS), by presenting the different elements of the kit, and relating them to actual robot components and norms. Furthermore a comparison between the LCS and Java is made, as well as comparing the RCX board to other technologies, specifically LEGO \textregistered NXT and MIT's "Handy Board". Also, concrete examples of application using the RIS are presented.
The Lego Mindstorms Robotics Invention Systems 2.0 Toolkit: A Study Case
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Human muscle fatigue is considered to be one of the main reasons for Musculoskeletal Disorder (MSD). Recent models have been introduced to define muscle fatigue for static postures. However, the main drawbacks of these models are that the dynamic effect of the human and the external load are not taken into account. In this paper, each human joint is assumed to be controlled by two muscle groups to generate motions such as push/pull. The joint torques are computed using Lagrange's formulation to evaluate the dynamic factors of the muscle fatigue model. An experiment is defined to validate this assumption and the result for one person confirms its feasibility. The evaluation of this model can predict the fatigue and MSD risk in industry production quickly.
Human Muscle Fatigue Model in Dynamic Motions
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The paper is devoted to the compliance errors compensation for parallel manipulators under external loading. Proposed approach is based on the non-linear stiffness modeling and reduces to a proper adjusting of a target trajectory. In contrast to previous works, in addition to compliance errors caused by machining forces, the problem of assembling errors caused by inaccuracy in the kinematic chains is considered. The advantages and practical significance of the proposed approach are illustrated by examples that deal with groove milling with Orthoglide manipulator.
Compensation of compliance errors in parallel manipulators composed of non-perfect kinematic chains
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This paper proposes a new design method to determine the feasible set of parameters of translational or position/orientation decoupled parallel robots for a prescribed singularity-free workspace of regular shape. The suggested method uses Groebner bases to define the singularities and the cylindrical algebraic decomposition to characterize the set of parameters. It makes it possible to generate all the robot designs. A 3-RRR decoupled robot is used to validate the proposed design method.
Solution regions in the parameter space of a 3-RRR decoupled robot for a prescribed workspace
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This paper investigates the conditions in the design parameter space for the existence and distribution of the cusp locus for planar parallel manipulators. Cusp points make possible non-singular assembly-mode changing motion, which increases the maximum singularity-free workspace. An accurate algorithm for the determination is proposed amending some imprecisions done by previous existing algorithms. This is combined with methods of Cylindric Algebraic Decomposition, Gr\"obner bases and Discriminant Varieties in order to partition the parameter space into cells with constant number of cusp points. These algorithms will allow us to classify a family of degenerate 3-RPR manipulators.
Cusp Points in the Parameter Space of Degenerate 3-RPR Planar Parallel Manipulators
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Motion planning problems have been studied by both the robotics and the controls research communities for a long time, and many algorithms have been developed for their solution. Among them, incremental sampling-based motion planning algorithms, such as the Rapidly-exploring Random Trees (RRTs), and the Probabilistic Road Maps (PRMs) have become very popular recently, owing to their implementation simplicity and their advantages in handling high-dimensional problems. Although these algorithms work very well in practice, the quality of the computed solution is often not good, i.e., the solution can be far from the optimal one. A recent variation of RRT, namely the RRT* algorithm, bypasses this drawback of the traditional RRT algorithm, by ensuring asymptotic optimality as the number of samples tends to infinity. Nonetheless, the convergence rate to the optimal solution may still be slow. This paper presents a new incremental sampling-based motion planning algorithm based on Rapidly-exploring Random Graphs (RRG), denoted RRT# (RRT "sharp") which also guarantees asymptotic optimality but, in addition, it also ensures that the constructed spanning tree of the geometric graph is consistent after each iteration. In consistent trees, the vertices which have the potential to be part of the optimal solution have the minimum cost-come-value. This implies that the best possible solution is readily computed if there are some vertices in the current graph that are already in the goal region. Numerical results compare with the RRT* algorithm.
The Role of Vertex Consistency in Sampling-based Algorithms for Optimal Motion Planning
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Understanding object and its context are very important for robots when dealing with objects for completion of a mission. In this paper, an Affordance-based Ontology (ABO) is proposed for easy robot dealing with substantive and non-substantive objects. An ABO is a machine-understandable representation of objects and their relationships by what it's related to and how it's related. By using ABO, when dealing with a substantive object, robots can understand the representation of its object and its relation with other non-substantive objects. When the substantive object is not available, the robots have the understanding ability, in term of objects and their functions to select a non substantive object in order to complete the mission, such as giving raincoat or hat instead of getting stuck due to the unavailability of substantive object, e.g. umbrella. The experiment is done in the Ubiquitous Robotics Technology (u-RT) Space of National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan.
An Approach For Robots To Deal With Objects
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The optimal disturbance rejection control problem is considered for consensus tracking systems affected by external persistent disturbances and noise. Optimal estimated values of system states are obtained by recursive filtering for the multiple autonomous underwater vehicles modeled to multi-agent systems with Kalman filter. Then the feedforward-feedback optimal control law is deduced by solving the Riccati equations and matrix equations. The existence and uniqueness condition of feedforward-feedback optimal control law is proposed and the optimal control law algorithm is carried out. Lastly, simulations show the result is effectiveness with respect to external persistent disturbances and noise.
An optimal consensus tracking control algorithm for autonomous underwater vehicles with disturbances
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Sensor fusion of multiple sources plays an important role in vehicular systems to achieve refined target position and velocity estimates. In this article, we address the general registration problem, which is a key module for a fusion system to accurately correct systematic errors of sensors. A fast maximum a posteriori (FMAP) algorithm for joint registration-tracking (JRT) is presented. The algorithm uses a recursive two-step optimization that involves orthogonal factorization to ensure numerically stability. Statistical efficiency analysis based on Cram\`{e}r-Rao lower bound theory is presented to show asymptotical optimality of FMAP. Also, Givens rotation is used to derive a fast implementation with complexity O(n) with $n$ the number of tracked targets. Simulations and experiments are presented to demonstrate the promise and effectiveness of FMAP.
Fast Optimal Joint Tracking-Registration for Multi-Sensor Systems
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This paper investigates the use of depth images as localisation sensors for 3D map building. The localisation information is derived from the 3D data thanks to the ICP (Iterative Closest Point) algorithm. The covariance of the ICP, and thus of the localization error, is analysed, and described by a Fisher Information Matrix. It is advocated this error can be much reduced if the data is fused with measurements from other motion sensors, or even with prior knowledge on the motion. The data fusion is performed by a recently introduced specific extended Kalman filter, the so-called Invariant EKF, and is directly based on the estimated covariance of the ICP. The resulting filter is very natural, and is proved to possess strong properties. Experiments with a Kinect sensor and a three-axis gyroscope prove clear improvement in the accuracy of the localization, and thus in the accuracy of the built 3D map.
Accurate 3D maps from depth images and motion sensors via nonlinear Kalman filtering
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This paper presents a visual tracking system that is capable or running real time on-board a small UAV (Unmanned Aerial Vehicle). The tracking system is computationally efficient and invariant to lighting changes and rotation of the object or the camera. Detection and tracking is autonomously carried out on the payload computer and there are two different methods for creation of the image patches. The first method starts detecting and tracking using a stored image patch created prior to flight with previous flight data. The second method allows the operator on the ground to select the interest object for the UAV to track. The tracking system is capable of re-detecting the object of interest in the events of tracking failure. Performance of the tracking system was verified both in the lab and during actual flights of the UAV. Results show that the system can run on-board and track a diverse set of objects in real time.
Implementation of an Onboard Visual Tracking System with Small Unmanned Aerial Vehicle (UAV)
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Low-cost sensing gloves for reconstruction posture provide measurements which are limited under several regards. They are generated through an imperfectly known model, are subject to noise, and may be less than the number of Degrees of Freedom (DoFs) of the hand. Under these conditions, direct reconstruction of the hand posture is an ill-posed problem, and performance can be very poor. This paper examines the problem of estimating the posture of a human hand using(low-cost) sensing gloves, and how to improve their performance by exploiting the knowledge on how humans most frequently use their hands. To increase the accuracy of pose reconstruction without modifying the glove hardware - hence basically at no extra cost - we propose to collect, organize, and exploit information on the probabilistic distribution of human hand poses in common tasks. We discuss how a database of such an a priori information can be built, represented in a hierarchy of correlation patterns or postural synergies, and fused with glove data in a consistent way, so as to provide a good hand pose reconstruction in spite of insufficient and inaccurate sensing data. Simulations and experiments on a low-cost glove are reported which demonstrate the effectiveness of the proposed techniques.
Synergy-based Hand Pose Sensing: Reconstruction Enhancement
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In this paper we study the problem of improving human hand pose sensing device performance by exploiting the knowledge on how humans most frequently use their hands in grasping tasks. In a companion paper we studied the problem of maximizing the reconstruction accuracy of the hand pose from partial and noisy data provided by any given pose sensing device (a sensorized "glove") taking into account statistical a priori information. In this paper we consider the dual problem of how to design pose sensing devices, i.e. how and where to place sensors on a glove, to get maximum information about the actual hand posture. We study the continuous case, whereas individual sensing elements in the glove measure a linear combination of joint angles, the discrete case, whereas each measure corresponds to a single joint angle, and the most general hybrid case, whereas both continuous and discrete sensing elements are available. The objective is to provide, for given a priori information and fixed number of measurements, the optimal design minimizing in average the reconstruction error. Solutions relying on the geometrical synergy definition as well as gradient flow-based techniques are provided. Simulations of reconstruction performance show the effectiveness of the proposed optimal design.
Synergy-Based Hand Pose Sensing: Optimal Glove Design
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We consider the problem of carrier-phase differential GPS positioning for an land vehicle navigation system (LVNS), tightly coupled with an inertial measurement unit (IMU) and a speedometer. The primary focus is to apply Bayesian network to an IMU-aided GPS positioning system based on carrier-phase differential GPS. We describe the implementation details of the positioning system that integrates GPS measurements (i.e., pseudo-range, carrier-phase and doppler), IMU measurements, and speedometer measurements. We derive the linearized state process equation and the measurement equation for GPS and speedometer. To account for constraints of land vehicle, we add two more pseudo measurements to ensure the perpendicular velocities close to zero.
An IMU-Aided Carrier-Phase Differential GPS Positioning System
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During the conceptual and prototype design stage of an industrial product, it is crucial to take assembly/disassembly and maintenance operations in advance. A well-designed system should enable relatively easy access of operating manipulators in the constrained environment and reduce musculoskeletal disorder risks for those manual handling operations. Trajectory planning comes up as an important issue for those assembly and maintenance operations under a constrained environment, since it determines the accessibility and the other ergonomics issues, such as muscle effort and its related fatigue. In this paper, a customer-oriented interactive approach is proposed to partially solve ergonomic related issues encountered during the design stage under a constrained system for the operator's convenience. Based on a single objective optimization method, trajectory planning for different operators could be generated automatically. Meanwhile, a motion capture based method assists the operator to guide the trajectory planning interactively when either a local minimum is encountered within the single objective optimization or the operator prefers guiding the virtual human manually. Besides that, a physical engine is integrated into this approach to provide physically realistic simulation in real time manner, so that collision free path and related dynamic information could be computed to determine further muscle fatigue and accessibility of a product design
Human Arm simulation for interactive constrained environment design
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Pushing/Pulling tasks is an important part of work in many industries. Usually, most researchers study the Push/Pull tasks by analyzing different posture conditions, force requirements, velocity factors, etc. However few studies have reported the effects of fatigue. Fatigue caused by physical loading is one of the main reasons responsible for MusculoSkeletal Disorders (MSD). In this paper, muscle groups of articulation is considered and from joint level a new approach is proposed for muscle fatigue evaluation in the arms Push/Pull operations. The objective of this work is to predict the muscle fatigue situation in the Push/Pull tasks in order to reduce the probability of MSD problems for workers. A case study is presented to use this new approach for analyzing arm fatigue in Pushing/Pulling.
A new approach to muscle fatigue evaluation for Push/Pull task
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The in-flight alignment is a critical stage for airborne INS/GPS applications. The alignment task is usually carried out by the Kalman filtering technique that necessitates a good initial attitude to obtain satisfying performance. Due to the airborne dynamics, the in-flight alignment is much difficult than alignment on the ground. This paper proposes an optimization-based coarse alignment approach using GPS position/velocity as input, founded on the newly-derived velocity/position integration formulae. Simulation and flight test results show that, with the GPS lever arm well handled, it is potentially able to yield the initial heading up to one degree accuracy in ten seconds. It can serve as a nice coarse in-flight alignment without any prior attitude information for the subsequent fine Kalman alignment. The approach can also be applied to other applications that require aligning the INS on the run.
Velocity/Position Integration Formula (I): Application to In-flight Coarse Alignment
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Inertial navigation applications are usually referenced to a rotating frame. Consideration of the navigation reference frame rotation in the inertial navigation algorithm design is an important but so far less seriously treated issue, especially for ultra-high-speed flying aircraft or the future ultra-precision navigation system of several meters per hour. This paper proposes a rigorous approach to tackle the issue of navigation frame rotation in velocity/position computation by use of the newly-devised velocity/position integration formulae in the Part I companion paper. The two integration formulae set a well-founded cornerstone for the velocity/position algorithms design that makes the comprehension of the inertial navigation computation principle more accessible to practitioners, and different approximations to the integrals involved will give birth to various velocity/position update algorithms. Two-sample velocity and position algorithms are derived to exemplify the design process. In the context of level-flight airplane examples, the derived algorithm is analytically and numerically compared to the typical algorithms existing in the literature. The results throw light on the problems in existing algorithms and the potential benefits of the derived algorithm.
Velocity/Position Integration Formula (II): Application to Inertial Navigation Computation
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In this paper, we consider the automated planning of optimal paths for a robotic team satisfying a high level mission specification. Each robot in the team is modeled as a weighted transition system where the weights have associated deviation values that capture the non-determinism in the traveling times of the robot during its deployment. The mission is given as a Linear Temporal Logic (LTL) formula over a set of propositions satisfied at the regions of the environment. Additionally, we have an optimizing proposition capturing some particular task that must be repeatedly completed by the team. The goal is to minimize the maximum time between successive satisfying instances of the optimizing proposition while guaranteeing that the mission is satisfied even under non-deterministic traveling times. Our method relies on the communication capabilities of the robots to guarantee correctness and maintain performance during deployment. After computing a set of optimal satisfying paths for the members of the team, we also compute a set of synchronization sequences for each robot to ensure that the LTL formula is never violated during deployment. We implement and experimentally evaluate our method considering a persistent monitoring task in a road network environment.
Optimal Multi-Robot Path Planning with LTL Constraints: Guaranteeing Correctness Through Synchronization
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Observability is a key aspect of the state estimation problem of SLAM, However, the dimension and variables of SLAM system might be changed with new features, to which little attention is paid in the previous work. In this paper, a unified approach of observability analysis for SLAM system is provided, whether the dimension and variables of SLAM system are changed or not, we can use this approach to analyze the local or total observability of the SLAM system.
A Unified Approach of Observability Analysis for Airborne SLAM
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Our goal in this paper is to plan the motion of a robot in a partitioned environment with dynamically changing, locally sensed rewards. We assume that arbitrary assumptions on the reward dynamics can be given. The robot aims to accomplish a high-level temporal logic surveillance mission and to locally optimize the collection of the rewards in the visited regions. These two objectives often conflict and only a compromise between them can be reached. We address this issue by taking into consideration a user-defined preference function that captures the trade-off between the importance of collecting high rewards and the importance of making progress towards a surveyed region. Our solution leverages ideas from the automata-based approach to model checking. We demonstrate the utilization and benefits of the suggested framework in an illustrative example.
Attraction-Based Receding Horizon Path Planning with Temporal Logic Constraints
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Many robotic systems deal with uncertainty by performing a sequence of information gathering actions. In this work, we focus on the problem of efficiently constructing such a sequence by drawing an explicit connection to submodularity. Ideally, we would like a method that finds the optimal sequence, taking the minimum amount of time while providing sufficient information. Finding this sequence, however, is generally intractable. As a result, many well-established methods select actions greedily. Surprisingly, this often performs well. Our work first explains this high performance -- we note a commonly used metric, reduction of Shannon entropy, is submodular under certain assumptions, rendering the greedy solution comparable to the optimal plan in the offline setting. However, reacting online to observations can increase performance. Recently developed notions of adaptive submodularity provide guarantees for a greedy algorithm in this online setting. In this work, we develop new methods based on adaptive submodularity for selecting a sequence of information gathering actions online. In addition to providing guarantees, we can capitalize on submodularity to attain additional computational speedups. We demonstrate the effectiveness of these methods in simulation and on a robot.
Efficient Touch Based Localization through Submodularity
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Many tasks in robotics can be decomposed into sub-tasks that are performed simultaneously. In many cases, these sub-tasks cannot all be achieved jointly and a prioritization of such sub-tasks is required to resolve this issue. In this paper, we discuss a novel learning approach that allows to learn a prioritized control law built on a set of sub-tasks represented by motor primitives. The primitives are executed simultaneously but have different priorities. Primitives of higher priority can override the commands of the conflicting lower priority ones. The dominance structure of these primitives has a significant impact on the performance of the prioritized control law. We evaluate the proposed approach with a ball bouncing task on a Barrett WAM.
Learning Prioritized Control of Motor Primitives
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We address the problem of controlling a noisy differential drive mobile robot such that the probability of satisfying a specification given as a Bounded Linear Temporal Logic (BLTL) formula over a set of properties at the regions in the environment is maximized. We assume that the vehicle can determine its precise initial position in a known map of the environment. However, inspired by practical limitations, we assume that the vehicle is equipped with noisy actuators and, during its motion in the environment, it can only measure the angular velocity of its wheels using limited accuracy incremental encoders. Assuming the duration of the motion is finite, we map the measurements to a Markov Decision Process (MDP). We use recent results in Statistical Model Checking (SMC) to obtain an MDP control policy that maximizes the probability of satisfaction. We translate this policy to a vehicle feedback control strategy and show that the probability that the vehicle satisfies the specification in the environment is bounded from below by the probability of satisfying the specification on the MDP. We illustrate our method with simulations and experimental results.
Control of Noisy Differential-Drive Vehicles from Time-Bounded Temporal Logic Specifications
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Recursive matrix relations for the complete dynamics of a 3-PRP planar parallel robot are established in this paper. Three identical planar legs connecting to the moving platform are located in the same vertical plane. Knowing the motion of the platform, we develop first the inverse kinematical problem and determine the positions, velocities and accelerations of the robot. Further, the inverse dynamic problem is solved using an approach based on the principle of virtual work. Finally, some graphs of simulation for the input powers of three actuators and the internal joint forces are obtained.
Internal joint forces in dynamics of a 3-PRP planar parallel robot
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In this paper, we analyze the robustness of the PSO-based approach to parameter estimation of robot dynamics presented in Part One. We have made attempts to make the PSO method more robust by experimenting with potential cost functions. The simulated system is a cylindrical robot; through simulation, the robot is excited, samples are taken, error is added to the samples, and the noisy samples are used for estimating the robot parameters through the presented method. Comparisons are made with the least squares, total least squares, and robust least squares methods of estimation.
Use of PSO in Parameter Estimation of Robot Dynamics; Part Two: Robustness
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This paper illustrates how a 3 degrees of freedom, Cartesian robot can be given the task of playing ping pong against a human player. We present an algorithm based on particle swarm optimization for the robot to calculate when and how to hit an approaching ball. Simulation results are shown to depict the effectiveness of our approach. Although emphasis is placed on sending the ball to a desired point on the ping pong table, it is shown that our method may be adjusted to meet the requirements of a variety of ball hitting strategies.
Ball Striking Algorithm for a 3 DOF Ping-Pong Playing Robot Based on Particle Swarm Optimization
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Offline procedures for estimating parameters of robot dynamics are practically based on the parameterized inverse dynamic model. In this paper, we present a novel approach to parameter estimation of robot dynamics which removes the necessity of parameterization (i.e. finding the minimum number of parameters from which the dynamics can be calculated through a linear model with respect to these parameters). This offline approach is based on a simple and powerful swarm intelligence tool: the particle swarm optimization (PSO). In this paper, we discuss and validate the method through simulated experiments. In Part Two we analyze our method in terms of robustness and compare it to robust analytical methods of estimation.
Use of PSO in Parameter Estimation of Robot Dynamics; Part One: No Need for Parameterization
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The paper focuses on the calibration of elastostatic parameters of spatial anthropomorphic robots. It proposes a new strategy for optimal selection of the measurement configurations that essentially increases the efficiency of robot calibration. This strategy is based on the concept of the robot test-pose and ensures the best compliance error compensation for the test configuration. The advantages of the proposed approach and its suitability for practical applications are illustrated by numerical examples, which deal with calibration of elastostatic parameters of a 3 degrees of freedom anthropomorphic manipulator with rigid links and compliant actuated joints
Optimal Selection of Measurement Configurations for Stiffness Model Calibration of Anthropomorphic Manipulators
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The paper focuses on the accuracy improvement of geometric and elasto-static calibration of industrial robots. It proposes industry-oriented performance measures for the calibration experiment design. They are based on the concept of manipulator test-pose and referred to the end-effector location accuracy after application of the error compensation algorithm, which implements the identified parameters. This approach allows the users to define optimal measurement configurations for robot calibration for given work piece location and machining forces/torques. These performance measures are suitable for comparing the calibration plans for both simple and complex trajectories to be performed. The advantages of the developed techniques are illustrated by an example that deals with machining using robotic manipulator.
Industry-oriented Performance Measures for Design of Robot Calibration Experiment
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The paper presents the compliance errors compensation technique for over-constrained parallel manipulators under external and internal loadings. This technique is based on the non-linear stiffness modeling which is able to take into account the influence of non-perfect geometry of serial chains caused by manufacturing errors. Within the developed technique, the deviation compensation reduces to an adjustment of a target trajectory that is modified in the off-line mode. The advantages and practical significance of the proposed technique are illustrated by an example that deals with groove milling by the Orthoglide manipulator that considers different locations of the workpiece. It is also demonstrated that the impact of the compliance errors and the errors caused by inaccuracy in serial chains cannot be taken into account using the superposition principle.
Compliance error compensation technique for parallel robots composed of non-perfect serial chains
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The paper focuses on the stiffness modeling of parallel manipulators composed of non-perfect serial chains, whose geometrical parameters differ from the nominal ones. In these manipulators, there usually exist essential internal forces/torques that considerably affect the stiffness properties and also change the end-effector location. These internal load-ings are caused by elastic deformations of the manipulator ele-ments during assembling, while the geometrical errors in the chains are compensated for by applying appropriate forces. For this type of manipulators, a non-linear stiffness modeling tech-nique is proposed that allows us to take into account inaccuracy in the chains and to aggregate their stiffness models for the case of both small and large deflections. Advantages of the developed technique and its ability to compute and compensate for the compliance errors caused by different factors are illustrated by an example that deals with parallel manipulators of the Or-thoglide family
Stiffness modeling of non-perfect parallel manipulators
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The paper is devoted to the elastostatic calibration of industrial robots, which is used for precise machining of large-dimensional parts made of composite materials. In this technological process, the interaction between the robot and the workpiece causes essential elastic deflections of the manipulator components that should be compensated by the robot controller using relevant elastostatic model of this mechanism. To estimate parameters of this model, an advanced calibration technique is applied that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, it is proposed a concept of the user-defined test-pose, which is used to evaluate the calibration experiments quality. In the frame of this concept, the related optimization problem is defined and numerical routines are developed, which allow generating optimal set of manipulator configurations and corresponding forces/torques for a given number of the calibration experiments. Some specific kinematic constraints are also taken into account, which insure feasibility of calibration experiments for the obtained configurations and allow avoiding collision between the robotic manipulator and the measurement equipment. The efficiency of the developed technique is illustrated by an application example that deals with elastostatic calibration of the serial manipulator used for robot-based machining.
Design of Calibration Experiments for Identification of Manipulator Elastostatic Parameters
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The paper is devoted to the geometrical calibration of industrial robots employed in precise manufacturing. To identify geometric parameters, an advanced calibration technique is proposed that is based on the non-linear experiment design theory, which is adopted for this particular application. In contrast to previous works, the calibration experiment quality is evaluated using a concept of the user-defined test-pose. In the frame of this concept, the related optimization problem is formulated and numerical routines are developed, which allow user to generate optimal set of manipulator configurations for a given number of calibration experiments. The efficiency of the developed technique is illustrated by several examples.
Optimization of measurement configurations for geometrical calibration of industrial robot
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The paper presents a novel technique for the design of optimal calibration experiments for a planar anthropomorphic manipulator with n degrees of freedom. Proposed approach for selection of manipulator configurations allows essentially improving calibration accuracy and reducing parameter identification errors. The results are illustrated by application examples that deal with typical anthropomorphic manipulators.
Design of Experiments for Calibration of Planar Anthropomorphic Manipulators
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In this chapter we will highlight our experimental studies on natural human walking analysis and introduce a biologically inspired design for simple bipedal locomotion system of humanoid robots. Inspiration comes directly from human walking analysis and human muscles mechanism and control. A hybrid algorithm for walking gaits generation is then proposed as an innovative alternative to classically used kinematics and dynamic equations solving, the gaits include knee, ankle and hip trajectories. The proposed algorithm is an intelligent evolutionary based on particle swarm optimization paradigm. This proposal can be used for small size humanoid robots, with a knee an ankle and a hip and at least six Degrees of Freedom (DOF).
Toward Intelligent Biped-Humanoids Gaits Generation
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Proceedings of the Second International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob'11), held in conjunction with the 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2011), September 2011 in San Francisco, USA. The main topics of the workshop were Domain-Specific Languages (DSLs) and Model-driven Software Development (MDSD) for robotics. A domain-specific language (DSL) is a programming language dedicated to a particular problem domain that offers specific notations and abstractions that increase programmer productivity within that domain. Models offer a high-level way for domain users to specify the functionality of their system at the right level of abstraction. DSLs and models have historically been used for programming complex systems. However recently they have garnered interest as a separate field of study. Robotic systems blend hardware and software in a holistic way that intrinsically raises many crosscutting concerns (concurrency, uncertainty, time constraints, ...), for which reason, traditional general-purpose languages often lead to a poor fit between the language features and the implementation requirements. DSLs and models offer a powerful, systematic way to overcome this problem, enabling the programmer to quickly and precisely implement novel software solutions to complex problems
Proceedings of the Second International Workshop on Domain-Specific Languages and Models for Robotic Systems (DSLRob 2011)
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Nowadays, vehicle safety is constantly increasing thanks to the improvement of vehicle passive and active safety. However, on a daily usage of the car, traffic jams remains a problem. With limited space for road infrastructure, automation of the driving task on specific situation seems to be a possible solution. The French project ABV, which stands for low speed automation, tries to demonstrate the feasibility of the concept and to prove the benefits. In this article, we describe the scientific background of the project and expected outputs.
Low Speed Automation, a French Initiative
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