license: mit
task_categories:
- robotics
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: trajectories
list: float64
- name: c_data
list: float64
- name: samples
list:
list:
list:
list: float64
- name: dsamples
list:
list:
list:
list: float64
- name: t_samples
list:
list: float64
splits:
- name: train
num_bytes: 187797344364
num_examples: 199099
download_size: 177769694322
dataset_size: 187797344364
SafeFlowMPC Finetuning Dataset
This repository contains the finetuning dataset used in the paper SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies.
SafeFlowMPC is a method that combines flow matching and online optimization to achieve safe and flexible robotic manipulation. This specific dataset is used for the finetuning stage to incorporate safety considerations into the model.
- Paper: SafeFlowMPC: Predictive and Safe Trajectory Planning for Robot Manipulators with Learning-based Policies
- Code: SafeFlowMPC GitHub
- Project Page: https://www.acin.tuwien.ac.at/en/42d6
Usage
This dataset is designed to be used with the SafeFlowMPC training scripts. To finetune a model on this dataset with safety considerations, you can use the following command from the official repository:
python train_imitation_learning_safe.py
The script is configured to load this dataset automatically from the Hugging Face Hub.
Dataset Creation
The dataset was created using the VP-STO planner. It contains safe intermediate trajectories generated to train the flow matching model for precise and safe robotic tasks, such as grasping and human-robot object handovers on a KUKA 7-DoF manipulator.