Differentiable Soft-Robot Generation

Author:

Cochevelou François1ORCID,Bonner David1ORCID,Schmidt Martin-Pierre12ORCID

Affiliation:

1. Dassault Systèmes, Vélizy-Villacoublay, France

2. Mathematics lab (LMI), National Institute of Applied Sciences (INSA), Rouen, France

Publisher

ACM

Reference33 articles.

1. Martin Philip Bendsøe and Ole Sigmund . 2003. Topology Optimization - Theory, Methods, and Applications . Springer Verlag , Germany . Martin Philip Bendsøe and Ole Sigmund. 2003. Topology Optimization - Theory, Methods, and Applications. Springer Verlag, Germany.

2. Jagdeep Bhatia , Holly Jackson , Yunsheng Tian , Jie Xu , and Wojciech Matusik . 2021. Evolution gym: A large-scale benchmark for evolving soft robots. Advances in Neural Information Processing Systems 34 ( 2021 ). Jagdeep Bhatia, Holly Jackson, Yunsheng Tian, Jie Xu, and Wojciech Matusik. 2021. Evolution gym: A large-scale benchmark for evolving soft robots. Advances in Neural Information Processing Systems 34 (2021).

3. Projective dynamics

4. Scalable co-optimization of morphology and control in embodied machines

5. Unshackling evolution

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1. Computational synthesis of locomotive soft robots by topology optimization;Science Advances;2024-07-26

2. Reinforcement learning for freeform robot design;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

3. Robustness in Diversity: Quality-Diversity Driven Discovery of Agile Soft Robotic Gaits;2024 IEEE 7th International Conference on Soft Robotics (RoboSoft);2024-04-14

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