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 SE(3) . 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, eit...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Institute of Electrical and Electronics Engineers (IEEE)
2022
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| Online Access: | https://hdl.handle.net/1721.1/139676 |
| _version_ | 1826211198725521408 |
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| author | Culbertson, Preston Slotine, Jean-Jacques Schwager, Mac |
| author2 | Massachusetts Institute of Technology. Department of Mechanical Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Mechanical Engineering Culbertson, Preston Slotine, Jean-Jacques Schwager, Mac |
| author_sort | Culbertson, Preston |
| collection | MIT |
| description | In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in SE(3) . 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. |
| first_indexed | 2024-09-23T15:02:27Z |
| format | Article |
| id | mit-1721.1/139676 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T15:02:27Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1396762023-06-12T18:01:26Z Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies Culbertson, Preston Slotine, Jean-Jacques Schwager, Mac Massachusetts Institute of Technology. Department of Mechanical Engineering Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences Massachusetts Institute of Technology. Department of Aeronautics and Astronautics In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in SE(3) . 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. 2022-01-24T19:20:42Z 2022-01-24T19:20:42Z 2021 2022-01-24T19:17:15Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/139676 Culbertson, Preston, Slotine, Jean-Jacques and Schwager, Mac. 2021. "Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies." IEEE Transactions on Robotics, 37 (6). en 10.1109/TRO.2021.3072021 IEEE Transactions on Robotics Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) arXiv |
| spellingShingle | Culbertson, Preston Slotine, Jean-Jacques Schwager, Mac Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title_full | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title_fullStr | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title_full_unstemmed | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title_short | Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies |
| title_sort | decentralized adaptive control for collaborative manipulation of rigid bodies |
| url | https://hdl.handle.net/1721.1/139676 |
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