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Consensus Complementarity Control for Multicontact MPC
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DOI：10.1109/TRO.2024.3435423.png)
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We propose a hybrid model predictive control algorithm, consensus complementarity control, for systems that make and break contact with their environment. Many state-of-the-art controllers for tasks, which require initiating contact with the environment, such as locomotion and manipulation, require a priori mode schedules or are too computationally complex to run at real-time rates. We present a method based on the alternating direction method of multipliers that is capable of high-speed reasoning over potential contact events. Via a consensus formulation, our approach enables parallelization of the contact scheduling problem. We validate our results on five numerical examples, including four high-dimensional frictional contact problems, and a physical experimentation on an underactuated multicontact system. We further demonstrate the effectiveness of our method on a physical experiment accomplishing a high-dimensional, multicontact manipulation task with a robot arm.
Keyword:
Contact modeling
dexterous manipulation
multicontact control
optimization and optimal control
Contact modeling
dexterous manipulation
multicontact control
optimization and optimal control
期刊
IF:
10.5
论文数:
3.3K
被引数:
2.8W
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