Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies
In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in <inline-formula><tex-math notation="LaTeX">\text{SE}(3)</tex-math></inline-formula>. The robots do not know the mass or friction properties of...
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| Published in: | IEEE transactions on robotics Vol. 37; no. 6; pp. 1906 - 1920 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
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New York
IEEE
01.12.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1552-3098, 1941-0468 |
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| Abstract | In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in <inline-formula><tex-math notation="LaTeX">\text{SE}(3)</tex-math></inline-formula>. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller's behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller's performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions. |
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| AbstractList | In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in [Formula Omitted]. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller’s behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller’s performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions. In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in <inline-formula><tex-math notation="LaTeX">\text{SE}(3)</tex-math></inline-formula>. The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller's behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller's performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions. |
| Author | Slotine, Jean-Jacques Culbertson, Preston Schwager, Mac |
| Author_xml | – sequence: 1 givenname: Preston orcidid: 0000-0002-1403-8697 surname: Culbertson fullname: Culbertson, Preston email: pculbertson@stanford.edu organization: Department of Mechanical Engineering, Stanford University, Stanford, CA, USA – sequence: 2 givenname: Jean-Jacques orcidid: 0000-0002-7161-7812 surname: Slotine fullname: Slotine, Jean-Jacques email: jjs@mit.edu organization: Department of Mechanical Engineering and the Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA – sequence: 3 givenname: Mac orcidid: 0000-0002-7871-3663 surname: Schwager fullname: Schwager, Mac email: schwager@stanford.edu organization: Department of Aeronautics and Astronautics, Stanford University, Stanford, CA, USA |
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| SubjectTerms | Adaptive control Algorithms Centroids Collaborative work Communication Controllers Cooperative manipulators distributed robot systems Initial conditions Manipulators Multi-robot systems multirobot systems Rigid structures Robots Robust control robust/adaptive control of robotic systems Trajectory Trajectory analysis |
| Title | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
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