Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints
<|reference_start|>Multi-finger Manipulation via Trajectory Optimization with Differentiable Rolling and Geometric Constraints: 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 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. Our method is tested in a peg alignment task and a screwdriver turning task, where it outperforms the 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, demonstrating its robustness to the sim2real gap.<|reference_end|>
@article{yang2024multi-finger,
    title={Multi-finger Manipulation via Trajectory Optimization with
  Differentiable Rolling and Geometric Constraints},
    author={Fan Yang, Thomas Power, Sergio Aguilera Marinovic, Soshi Iba, Rana
  Soltani Zarrin, Dmitry Berenson},
    journal={arXiv preprint arXiv:2408.13229},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.13229},
    primaryClass={cs.RO}
}