An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain
Autonomous unmanned surface vehicles (USVs) and unmanned underwater vehicles (UUVs) are becoming ubiquitous in applications exploring marine environments, and the design of path planning algorithms for these vehicles remains an open area of research. For marine environments, to save on energy a path...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/152742 |
| _version_ | 1826214290108973056 |
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| author | Largaespada, Raul Alexander |
| author2 | Leonard, John J. |
| author_facet | Leonard, John J. Largaespada, Raul Alexander |
| author_sort | Largaespada, Raul Alexander |
| collection | MIT |
| description | Autonomous unmanned surface vehicles (USVs) and unmanned underwater vehicles (UUVs) are becoming ubiquitous in applications exploring marine environments, and the design of path planning algorithms for these vehicles remains an open area of research. For marine environments, to save on energy a path between two points should be optimized to minimize distance traveled while remaining smooth to reduce changes in speed and account for the dynamic limits of the vehicle.
The Graphs of Convex Sets (GCS) trajectory optimization motion planner from the MIT Robot Locomotion Group is a recently developed planner which has been demonstrated to return smooth and optimal paths navigating around complex environments filled with obstacles, but this planner has not been applied to marine environments. The early successes of the GCS planner and the smoothness of the trajectories returned suggest that GCS could be effectively applied to USV and UUV path planning.
This project implemented the GCS planner as part of the MOOS-IvP so software suite for autonomous marine robotics. The robustness of the trajectories returned from GCS was evaluated via Monte Carlo trials on a simulated USV traversing a field of randomized known and unknown obstacles. The performance of GCS was compared against alternate planners implementing the D* Lite algorithm or relying only on existing MOOS-IvP obstacle avoidance capabilities, running the the same simulation environment.
In testing, the GCS planner was not as successful as the D* Lite planner in navigating dense obstacle fields, but returned smoother and shorter paths than D* Lite which were easier for the vehicle to follow. Testing also suggested future modifications to the GCS planner which could be added to further increase its robustness when applied to USVs operating in dense obstacle fields.
All code developed for this project may be found at: https://github.com/rlargaespada/moos-ivp-monte-carlo. |
| first_indexed | 2024-09-23T14:03:10Z |
| format | Thesis |
| id | mit-1721.1/152742 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T14:03:10Z |
| publishDate | 2023 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1527422023-11-03T03:25:41Z An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain Largaespada, Raul Alexander Leonard, John J. Bennett, Andrew Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Autonomous unmanned surface vehicles (USVs) and unmanned underwater vehicles (UUVs) are becoming ubiquitous in applications exploring marine environments, and the design of path planning algorithms for these vehicles remains an open area of research. For marine environments, to save on energy a path between two points should be optimized to minimize distance traveled while remaining smooth to reduce changes in speed and account for the dynamic limits of the vehicle. The Graphs of Convex Sets (GCS) trajectory optimization motion planner from the MIT Robot Locomotion Group is a recently developed planner which has been demonstrated to return smooth and optimal paths navigating around complex environments filled with obstacles, but this planner has not been applied to marine environments. The early successes of the GCS planner and the smoothness of the trajectories returned suggest that GCS could be effectively applied to USV and UUV path planning. This project implemented the GCS planner as part of the MOOS-IvP so software suite for autonomous marine robotics. The robustness of the trajectories returned from GCS was evaluated via Monte Carlo trials on a simulated USV traversing a field of randomized known and unknown obstacles. The performance of GCS was compared against alternate planners implementing the D* Lite algorithm or relying only on existing MOOS-IvP obstacle avoidance capabilities, running the the same simulation environment. In testing, the GCS planner was not as successful as the D* Lite planner in navigating dense obstacle fields, but returned smoother and shorter paths than D* Lite which were easier for the vehicle to follow. Testing also suggested future modifications to the GCS planner which could be added to further increase its robustness when applied to USVs operating in dense obstacle fields. All code developed for this project may be found at: https://github.com/rlargaespada/moos-ivp-monte-carlo. M.Eng. 2023-11-02T20:12:33Z 2023-11-02T20:12:33Z 2023-09 2023-10-03T18:21:15.801Z Thesis https://hdl.handle.net/1721.1/152742 0009-0005-0508-2919 In Copyright - Educational Use Permitted Copyright retained by author(s) https://rightsstatements.org/page/InC-EDU/1.0/ application/pdf Massachusetts Institute of Technology |
| spellingShingle | Largaespada, Raul Alexander An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title | An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title_full | An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title_fullStr | An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title_full_unstemmed | An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title_short | An Application of Graph of Convex Sets Trajectory Optimization to the Marine Robotics Domain |
| title_sort | application of graph of convex sets trajectory optimization to the marine robotics domain |
| url | https://hdl.handle.net/1721.1/152742 |
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