TR2023-024
Covariance Steering for Uncertain Contact-Rich Systems
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- "Covariance Steering for Uncertain Contact-Rich Systems", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/ICRA48891.2023.10160249, May 2023, pp. 7923-7929.BibTeX TR2023-024 PDF
- @inproceedings{Shirai2023may3,
- author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind},
- title = {Covariance Steering for Uncertain Contact-Rich Systems},
- booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
- year = 2023,
- pages = {7923--7929},
- month = may,
- publisher = {IEEE},
- doi = {10.1109/ICRA48891.2023.10160249},
- isbn = {979-8-3503-2365-8},
- url = {https://www.merl.com/publications/TR2023-024}
- }
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- "Covariance Steering for Uncertain Contact-Rich Systems", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/ICRA48891.2023.10160249, May 2023, pp. 7923-7929.
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MERL Contacts:
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Research Area:
Abstract:
Planning and control for uncertain contact sys- tems is challenging as it is not clear how to propagate uncertainty for planning. Contact-rich tasks can be modeled efficiently using complementarity constraints among other tech- niques. In this paper, we present a stochastic optimization technique with chance constraints for systems with stochastic complementarity constraints. We use a particle filter-based approach to propagate moments for stochastic complementarity system. To circumvent the issues of open-loop chance con- strained planning, we propose a contact-aware controller for covariance steering of the complementarity system. Our opti- mization problem is formulated as Non-Linear Programming (NLP) using bilevel optimization. We present an important- particle algorithm for numerical efficiency for the underlying control problem. We verify that our contact-aware closed-loop controller is able to steer the covariance of the states under stochastic contact-rich tasks.
Related News & Events
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NEWS MERL Researchers Present Thirteen Papers at the 2023 IEEE International Conference on Robotics and Automation (ICRA) Date: May 29, 2023 - June 2, 2023
Where: 2023 IEEE International Conference on Robotics and Automation (ICRA)
MERL Contacts: Anoop Cherian; Radu Corcodel; Siddarth Jain; Devesh K. Jha; Toshiaki Koike-Akino; Tim K. Marks; Daniel N. Nikovski; Arvind Raghunathan; Diego Romeres
Research Areas: Computer Vision, Machine Learning, Optimization, RoboticsBrief- MERL researchers will present thirteen papers, including eight main conference papers and five workshop papers, at the 2023 IEEE International Conference on Robotics and Automation (ICRA) to be held in London, UK from May 29 to June 2. ICRA is one of the largest and most prestigious conferences in the robotics community. The papers cover a broad set of topics in Robotics including estimation, manipulation, vision-based object recognition and segmentation, tactile estimation and tool manipulation, robotic food handling, robot skill learning, and model-based reinforcement learning.
In addition to the paper presentations, MERL robotics researchers will also host an exhibition booth and look forward to discussing our research with visitors.
- MERL researchers will present thirteen papers, including eight main conference papers and five workshop papers, at the 2023 IEEE International Conference on Robotics and Automation (ICRA) to be held in London, UK from May 29 to June 2. ICRA is one of the largest and most prestigious conferences in the robotics community. The papers cover a broad set of topics in Robotics including estimation, manipulation, vision-based object recognition and segmentation, tactile estimation and tool manipulation, robotic food handling, robot skill learning, and model-based reinforcement learning.
Related Publications
- @inproceedings{Shirai2023sep,
- author = {Shirai, Yuki and Jha, Devesh K. and Raghunathan, Arvind},
- title = {Contact-Aware Covariance Control of Stochastic Contact-Rich Systems},
- booktitle = {IROS 2023 Workshop on Leveraging Models for Contact-Rich Manipulation},
- year = 2023,
- month = sep,
- url = {https://www.merl.com/publications/TR2023-120}
- }