Distributed Motion Control for Multiple Connected Surface Vessels
© 2020 IEEE. We propose a scalable cooperative control approach which coordinates a group of rigidly connected autonomous surface vessels to track desired trajectories in a planar water environment as a single floating modular structure. Our approach leverages the implicit information of the structu...
| 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/1721.1/144040 |
| _version_ | 1826192332158926848 |
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| author | Wang, Wei Wang, Zijian Mateos, Luis Huang, Kuan Wei Schwager, Mac Ratti, Carlo Rus, Daniela |
| author2 | Senseable City Laboratory |
| author_facet | Senseable City Laboratory Wang, Wei Wang, Zijian Mateos, Luis Huang, Kuan Wei Schwager, Mac Ratti, Carlo Rus, Daniela |
| author_sort | Wang, Wei |
| collection | MIT |
| description | © 2020 IEEE. We propose a scalable cooperative control approach which coordinates a group of rigidly connected autonomous surface vessels to track desired trajectories in a planar water environment as a single floating modular structure. Our approach leverages the implicit information of the structure's motion for force and torque allocation without explicit communication among the robots. In our system, a leader robot steers the entire group by adjusting its force and torque according to the structure's deviation from the desired trajectory, while follower robots run distributed consensus-based controllers to match their inputs to amplify the leader's intent using only onboard sensors as feedback. To cope with the nonlinear system dynamics in the water, the leader robot employs a nonlinear model predictive controller (NMPC), where we experimentally estimated the dynamics model of the floating modular structure in order to achieve superior performance for leader-following control. Our method has a wide range of potential applications in transporting humans and goods in many of today's existing waterways. We conducted trajectory and orientation tracking experiments in hardware with three custom-built autonomous modular robotic boats, called Roboat, which are capable of holonomic motions and onboard state estimation. Simulation results with up to 65 robots also prove the scalability of our proposed approach. |
| first_indexed | 2024-09-23T09:10:08Z |
| format | Article |
| id | mit-1721.1/144040 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:10:08Z |
| publishDate | 2022 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1440402023-01-30T20:46:46Z Distributed Motion Control for Multiple Connected Surface Vessels Wang, Wei Wang, Zijian Mateos, Luis Huang, Kuan Wei Schwager, Mac Ratti, Carlo Rus, Daniela Senseable City Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory © 2020 IEEE. We propose a scalable cooperative control approach which coordinates a group of rigidly connected autonomous surface vessels to track desired trajectories in a planar water environment as a single floating modular structure. Our approach leverages the implicit information of the structure's motion for force and torque allocation without explicit communication among the robots. In our system, a leader robot steers the entire group by adjusting its force and torque according to the structure's deviation from the desired trajectory, while follower robots run distributed consensus-based controllers to match their inputs to amplify the leader's intent using only onboard sensors as feedback. To cope with the nonlinear system dynamics in the water, the leader robot employs a nonlinear model predictive controller (NMPC), where we experimentally estimated the dynamics model of the floating modular structure in order to achieve superior performance for leader-following control. Our method has a wide range of potential applications in transporting humans and goods in many of today's existing waterways. We conducted trajectory and orientation tracking experiments in hardware with three custom-built autonomous modular robotic boats, called Roboat, which are capable of holonomic motions and onboard state estimation. Simulation results with up to 65 robots also prove the scalability of our proposed approach. 2022-07-26T12:48:04Z 2022-07-26T12:48:04Z 2020 2022-07-26T12:29:32Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/144040 Wang, Wei, Wang, Zijian, Mateos, Luis, Huang, Kuan Wei, Schwager, Mac et al. 2020. "Distributed Motion Control for Multiple Connected Surface Vessels." IEEE International Conference on Intelligent Robots and Systems. en 10.1109/IROS45743.2020.9340743 IEEE International Conference on Intelligent Robots and Systems 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 | Wang, Wei Wang, Zijian Mateos, Luis Huang, Kuan Wei Schwager, Mac Ratti, Carlo Rus, Daniela Distributed Motion Control for Multiple Connected Surface Vessels |
| title | Distributed Motion Control for Multiple Connected Surface Vessels |
| title_full | Distributed Motion Control for Multiple Connected Surface Vessels |
| title_fullStr | Distributed Motion Control for Multiple Connected Surface Vessels |
| title_full_unstemmed | Distributed Motion Control for Multiple Connected Surface Vessels |
| title_short | Distributed Motion Control for Multiple Connected Surface Vessels |
| title_sort | distributed motion control for multiple connected surface vessels |
| url | https://hdl.handle.net/1721.1/144040 |
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