Consensus Complementarity Control for Multicontact MPC

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...

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Vydané v:	IEEE transactions on robotics Ročník 40; s. 3879 - 3896
Hlavní autori:	Aydinoglu, Alp, Wei, Adam, Huang, Wei-Cheng, Posa, Michael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 2024
Predmet:	Cognition Contact modeling dexterous manipulation Heuristic algorithms Mathematical models multicontact control optimization and optimal control Real-time systems Robots Task analysis Vectors
ISSN:	1552-3098, 1941-0468
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Abstract	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.
AbstractList	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.
Author	Aydinoglu, Alp Huang, Wei-Cheng Wei, Adam Posa, Michael
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Snippet	We propose a hybrid model predictive control algorithm, consensus complementarity control, for systems that make and break contact with their environment. Many...
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SubjectTerms	Cognition Contact modeling dexterous manipulation Heuristic algorithms Mathematical models multicontact control optimization and optimal control Real-time systems Robots Task analysis Vectors
Title	Consensus Complementarity Control for Multicontact MPC
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