Robotics: Science and Systems XVII
An End-to-End Differentiable Framework for Contact-Aware Robot Design
Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit AgrawalAbstract:
The current dominant paradigm for robotic manipulation involves two separate stages: manipulator design and control. Because the robot's morphology and how it can be controlled are intimately linked; joint optimization of design and control can significantly improve performance. Existing methods for co-optimization are limited and fail to explore a rich space of designs. The primary reason is the trade-off between the complexity of designs that is necessary for contact-rich tasks against the practical constraints of manufacturing; optimization; contact handling; etc. We overcome several of these challenges by building an end-to-end differentiable framework for contact-aware robot design. The two key components of this framework are: a novel deformation-based parameterization that allows for the design of articulated rigid robots with arbitrary; complex geometry; and a differentiable rigid body simulator that can handle contact-rich scenarios and computes analytical gradients for a full spectrum of kinematic and dynamic parameters. On multiple manipulation tasks; our framework outperforms existing methods that either only optimize for control or for design using alternate representations or co-optimize using gradient-free methods.
Bibtex:
@INPROCEEDINGS{Xu-RSS-21, AUTHOR = {Jie Xu AND Tao Chen AND Lara Zlokapa AND Michael Foshey AND Wojciech Matusik AND Shinjiro Sueda AND Pulkit Agrawal}, TITLE = {{An End-to-End Differentiable Framework for Contact-Aware Robot Design}}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2021}, ADDRESS = {Virtual}, MONTH = {July}, DOI = {10.15607/RSS.2021.XVII.008} }