Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916516236099584 |
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| author | Yang, Fan Power, Thomas Marinovic, Sergio Aguilera Iba, Soshi Zarrin, Rana Soltani Berenson, Dmitry |
| author_facet | Yang, Fan Power, Thomas Marinovic, Sergio Aguilera Iba, Soshi Zarrin, Rana Soltani Berenson, Dmitry |
| contents | Parameterizing finger rolling and finger-object contacts in a differentiable manner is important for formulating dexterous manipulation as a trajectory optimization problem. In contrast to previous methods which often assume simplified geometries of the robot and object or do not explicitly model finger rolling, we propose a method to further extend the capabilities of dexterous manipulation by accounting for non-trivial geometries of both the robot and the object. By integrating the object's Signed Distance Field (SDF) with a sampling method, our method estimates contact and rolling-related variables in a differentiable manner and includes those in a trajectory optimization framework. This formulation naturally allows for the emergence of finger-rolling behaviors, enabling the robot to locally adjust the contact points. To evaluate our method, we introduce a benchmark featuring challenging multi-finger dexterous manipulation tasks, such as screwdriver turning and in-hand reorientation. Our method outperforms baselines in terms of achieving desired object configurations and avoiding dropping the object. We also successfully apply our method to a real-world screwdriver turning task and a cuboid alignment task, demonstrating its robustness to the sim2real gap. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_13229 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints Yang, Fan Power, Thomas Marinovic, Sergio Aguilera Iba, Soshi Zarrin, Rana Soltani Berenson, Dmitry Robotics Parameterizing finger rolling and finger-object contacts in a differentiable manner is important for formulating dexterous manipulation as a trajectory optimization problem. In contrast to previous methods which often assume simplified geometries of the robot and object or do not explicitly model finger rolling, we propose a method to further extend the capabilities of dexterous manipulation by accounting for non-trivial geometries of both the robot and the object. By integrating the object's Signed Distance Field (SDF) with a sampling method, our method estimates contact and rolling-related variables in a differentiable manner and includes those in a trajectory optimization framework. This formulation naturally allows for the emergence of finger-rolling behaviors, enabling the robot to locally adjust the contact points. To evaluate our method, we introduce a benchmark featuring challenging multi-finger dexterous manipulation tasks, such as screwdriver turning and in-hand reorientation. Our method outperforms baselines in terms of achieving desired object configurations and avoiding dropping the object. We also successfully apply our method to a real-world screwdriver turning task and a cuboid alignment task, demonstrating its robustness to the sim2real gap. |
| title | Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints |
| topic | Robotics |
| url | https://arxiv.org/abs/2408.13229 |