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| | license: mit |
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| | # MaNI Series |
| | ``` |
| | The MaNI series is a real-world simulation dataset for robotic manipulation, focusing on complex |
| | human-object interaction and fine-grained motion modeling. This dataset systematically covers various manipulation |
| | types common in real-world robotic operation scenarios, including grasping, pushing, pulling, rotating, assembly, |
| | and tool use. It models real-world contact, friction, constraints, and dynamics through high-fidelity physical simulation. |
| | MaNI employs a multi-modal data acquisition and synchronization mechanism, including RGB/Depth visual observations, |
| | 6-DoF poses of objects and end-effectors, joint states, force/torque feedback, and continuous motion trajectories, |
| | providing rich and stable data support for learning end-to-end manipulation strategies from perception to control. |
| | Unlike purely simulated or purely real-world datasets, MaNI reduces the sim-to-real gap by reconstructing real-world |
| | scenarios and calibrating parameters in the simulation environment. This dataset is particularly suitable for research |
| | directions such as imitation learning, reinforcement learning, and manipulation planning, and can serve as an important |
| | benchmark for robotic skill learning, generalization ability evaluation, and complex interaction reasoning. |
| | ``` |
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| | MODAL : Data Confuser "Small files only" |
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| | CHARS : 517253f76213x0p |
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| | DCVERSION : 0.0.1.1 built 260209 |
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