Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle
© 2018 IEEE. In this paper, we present the design, modeling, and real-time nonlinear model predictive control (NMPC) of an autonomous robotic boat. The robot is easy to manufacture, highly maneuverable, and capable of accurate trajectory tracking in both indoor and outdoor environments. In particula...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021
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| Online Access: | https://hdl.handle.net/1721.1/137232 |
| _version_ | 1826198423385145344 |
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| author | Wang, Wei Mateos, Luis A. Park, Shinkyu Leoni, Pietro Gheneti, Banti Duarte, Fabio Ratti, Carlo Rus, Daniela |
| author2 | Senseable City Laboratory |
| author_facet | Senseable City Laboratory Wang, Wei Mateos, Luis A. Park, Shinkyu Leoni, Pietro Gheneti, Banti Duarte, Fabio Ratti, Carlo Rus, Daniela |
| author_sort | Wang, Wei |
| collection | MIT |
| description | © 2018 IEEE. In this paper, we present the design, modeling, and real-time nonlinear model predictive control (NMPC) of an autonomous robotic boat. The robot is easy to manufacture, highly maneuverable, and capable of accurate trajectory tracking in both indoor and outdoor environments. In particular, a cross type four-thruster configuration is proposed for the robotic boat to produce efficient holonomic motions. The robot prototype is rapidly 3D-printed and then sealed by adhering several layers of fiberglass. To achieve accurate tracking control, we formulate an NMPC strategy for the four-control-input boat with control input constraints, where the nonlinear dynamic model includes a Coriolis and centripetal matrix, the hydrodynamic added mass, and damping. By integrating 'GPS' modules and an inertial measurement unit (IMU) into the robot, we demonstrate accurate trajectory tracking of the robotic boat along preplanned paths in both a swimming pool and a natural river. Furthermore, the code generation strategy employed in our paper yields a two order of magnitude improvement in the run time of the NMPC algorithm compared to similar systems. The robot is designed to form the basis for surface swarm robotics testbeds, on which collective algorithms for surface transportation and self-assembly of dynamic floating infrastructures can be assessed. |
| first_indexed | 2024-09-23T11:04:39Z |
| format | Article |
| id | mit-1721.1/137232 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:04:39Z |
| publishDate | 2021 |
| publisher | IEEE |
| record_format | dspace |
| spelling | mit-1721.1/1372322023-02-09T15:59:04Z Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle Wang, Wei Mateos, Luis A. Park, Shinkyu Leoni, Pietro Gheneti, Banti Duarte, Fabio Ratti, Carlo Rus, Daniela Senseable City Laboratory Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory © 2018 IEEE. In this paper, we present the design, modeling, and real-time nonlinear model predictive control (NMPC) of an autonomous robotic boat. The robot is easy to manufacture, highly maneuverable, and capable of accurate trajectory tracking in both indoor and outdoor environments. In particular, a cross type four-thruster configuration is proposed for the robotic boat to produce efficient holonomic motions. The robot prototype is rapidly 3D-printed and then sealed by adhering several layers of fiberglass. To achieve accurate tracking control, we formulate an NMPC strategy for the four-control-input boat with control input constraints, where the nonlinear dynamic model includes a Coriolis and centripetal matrix, the hydrodynamic added mass, and damping. By integrating 'GPS' modules and an inertial measurement unit (IMU) into the robot, we demonstrate accurate trajectory tracking of the robotic boat along preplanned paths in both a swimming pool and a natural river. Furthermore, the code generation strategy employed in our paper yields a two order of magnitude improvement in the run time of the NMPC algorithm compared to similar systems. The robot is designed to form the basis for surface swarm robotics testbeds, on which collective algorithms for surface transportation and self-assembly of dynamic floating infrastructures can be assessed. 2021-11-03T16:12:15Z 2021-11-03T16:12:15Z 2018-05 2019-07-17T15:06:54Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137232 Wang, Wei, Mateos, Luis A., Park, Shinkyu, Leoni, Pietro, Gheneti, Banti et al. 2018. "Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle." en 10.1109/icra.2018.8460632 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf IEEE Other repository |
| spellingShingle | Wang, Wei Mateos, Luis A. Park, Shinkyu Leoni, Pietro Gheneti, Banti Duarte, Fabio Ratti, Carlo Rus, Daniela Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title | Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title_full | Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title_fullStr | Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title_full_unstemmed | Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title_short | Design, Modeling, and Nonlinear Model Predictive Tracking Control of a Novel Autonomous Surface Vehicle |
| title_sort | design modeling and nonlinear model predictive tracking control of a novel autonomous surface vehicle |
| url | https://hdl.handle.net/1721.1/137232 |
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