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Advanced soft robot modeling in ChainQueen

Author(s)
Spielberg, Andrew; Du, Tao; Hu, Yuanming; Rus, Daniela; Matusik, Wojciech
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Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/
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Abstract
<jats:title>Abstract</jats:title> <jats:p>We present extensions to ChainQueen, an open source, fully differentiable material point method simulator for soft robotics. Previous work established ChainQueen as a powerful tool for inference, control, and co-design for soft robotics. We detail enhancements to ChainQueen, allowing for more efficient simulation and optimization and expressive co-optimization over material properties and geometric parameters. We package our simulator extensions in an easy-to-use, modular application programming interface (API) with predefined observation models, controllers, actuators, optimizers, and geometric processing tools, making it simple to prototype complex experiments in 50 lines or fewer. We demonstrate the power of our simulator extensions in over nine simulated experiments.</jats:p>
Date issued
2021
URI
https://hdl.handle.net/1721.1/143792
Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Journal
Robotica
Publisher
Cambridge University Press (CUP)
Citation
Spielberg, Andrew, Du, Tao, Hu, Yuanming, Rus, Daniela and Matusik, Wojciech. 2021. "Advanced soft robot modeling in ChainQueen." Robotica.
Version: Final published version

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