Inverse Dynamics Trajectory Optimization for Contact-Implicit Model Predictive Control
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866916718183448576 |
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| author | Kurtz, Vince Castro, Alejandro Önol, Aykut Özgün Lin, Hai |
| author_facet | Kurtz, Vince Castro, Alejandro Önol, Aykut Özgün Lin, Hai |
| contents | Robots must make and break contact with the environment to perform useful tasks, but planning and control through contact remains a formidable challenge. In this work, we achieve real-time contact-implicit model predictive control with a surprisingly simple method: inverse dynamics trajectory optimization. While trajectory optimization with inverse dynamics is not new, we introduce a series of incremental innovations that collectively enable fast model predictive control on a variety of challenging manipulation and locomotion tasks. We implement these innovations in an open-source solver and present simulation examples to support the effectiveness of the proposed approach. Additionally, we demonstrate contact-implicit model predictive control on hardware at over 100 Hz for a 20-degree-of-freedom bi-manual manipulation task. Video and code are available at https://idto.github.io. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_01813 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Inverse Dynamics Trajectory Optimization for Contact-Implicit Model Predictive Control Kurtz, Vince Castro, Alejandro Önol, Aykut Özgün Lin, Hai Robotics Robots must make and break contact with the environment to perform useful tasks, but planning and control through contact remains a formidable challenge. In this work, we achieve real-time contact-implicit model predictive control with a surprisingly simple method: inverse dynamics trajectory optimization. While trajectory optimization with inverse dynamics is not new, we introduce a series of incremental innovations that collectively enable fast model predictive control on a variety of challenging manipulation and locomotion tasks. We implement these innovations in an open-source solver and present simulation examples to support the effectiveness of the proposed approach. Additionally, we demonstrate contact-implicit model predictive control on hardware at over 100 Hz for a 20-degree-of-freedom bi-manual manipulation task. Video and code are available at https://idto.github.io. |
| title | Inverse Dynamics Trajectory Optimization for Contact-Implicit Model Predictive Control |
| topic | Robotics |
| url | https://arxiv.org/abs/2309.01813 |