Autonomous Escort with an Unmanned Surface Vessel Using Model Predictive Control
(2026)Department of Automatic Control
- Abstract
- This thesis investigates the design and implementation of Model Predictive Control (MPC) and motion planning to enable an Unmanned Surface Vessel (USV) to perform autonomous escort missions. The objectives were to assess how the control architecture could utilize preexisting internal USV controllers and handle dynamic obstacles. Furthermore, how the controller architecture should be organized and how the controller performs when implemented on hardware were also explored. The proposed controller architecture consists of an MPC equipped with a generalized USV model to capture the unknown dynamics of the vessel where the model parameters are estimated online using an Extended Kalman Filter (EKF). The MPC is also equipped with a constraint... (More)
- This thesis investigates the design and implementation of Model Predictive Control (MPC) and motion planning to enable an Unmanned Surface Vessel (USV) to perform autonomous escort missions. The objectives were to assess how the control architecture could utilize preexisting internal USV controllers and handle dynamic obstacles. Furthermore, how the controller architecture should be organized and how the controller performs when implemented on hardware were also explored. The proposed controller architecture consists of an MPC equipped with a generalized USV model to capture the unknown dynamics of the vessel where the model parameters are estimated online using an Extended Kalman Filter (EKF). The MPC is also equipped with a constraint which handles dynamic collision-avoidance, and a station keeping P/PI controller to ensure that the USV stays in the target position. The motion planner utilizes a custom A* search algorithm coupled with B-splines to plan long-term global paths to avoid obstacles and find the shortest route to the target position. Three different MPC variations, utilizing the motion planner to different degrees, were tested and validated through simulations and experiments on the Mini-Piraya USV platform by Saab Kockums AB. The results presented show that all three proposed controller variants are capable of steering the USV with precision, validating that the USV model paired with the EKF gives a good approximation of the system dynamics when operating at low velocities. The collision-avoidance implementation in the controller shows good performance and the USV is always kept at a safe distance when navigating around the escorted vessel. The experimental results also show that the controllers perform well when subjected to environmental disturbances, sensor noise, and lag proving that this more general USV model could easily be adapted and applied to a real marine vessel. Overall, the results from both the simulations and the experiments show that all three MPC implementations can be used to accomplish the escort mission, with each one bringing slightly differing advantages and limitations. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/student-papers/record/9246237
- author
- Lagerstedt, Axel and Small, Sean
- supervisor
- organization
- year
- 2026
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6310
- other publication id
- 0280-5316
- language
- English
- id
- 9246237
- date added to LUP
- 2026-08-25 10:39:57
- date last changed
- 2026-08-25 10:39:57
@misc{9246237,
abstract = {{This thesis investigates the design and implementation of Model Predictive Control (MPC) and motion planning to enable an Unmanned Surface Vessel (USV) to perform autonomous escort missions. The objectives were to assess how the control architecture could utilize preexisting internal USV controllers and handle dynamic obstacles. Furthermore, how the controller architecture should be organized and how the controller performs when implemented on hardware were also explored. The proposed controller architecture consists of an MPC equipped with a generalized USV model to capture the unknown dynamics of the vessel where the model parameters are estimated online using an Extended Kalman Filter (EKF). The MPC is also equipped with a constraint which handles dynamic collision-avoidance, and a station keeping P/PI controller to ensure that the USV stays in the target position. The motion planner utilizes a custom A* search algorithm coupled with B-splines to plan long-term global paths to avoid obstacles and find the shortest route to the target position. Three different MPC variations, utilizing the motion planner to different degrees, were tested and validated through simulations and experiments on the Mini-Piraya USV platform by Saab Kockums AB. The results presented show that all three proposed controller variants are capable of steering the USV with precision, validating that the USV model paired with the EKF gives a good approximation of the system dynamics when operating at low velocities. The collision-avoidance implementation in the controller shows good performance and the USV is always kept at a safe distance when navigating around the escorted vessel. The experimental results also show that the controllers perform well when subjected to environmental disturbances, sensor noise, and lag proving that this more general USV model could easily be adapted and applied to a real marine vessel. Overall, the results from both the simulations and the experiments show that all three MPC implementations can be used to accomplish the escort mission, with each one bringing slightly differing advantages and limitations.}},
author = {{Lagerstedt, Axel and Small, Sean}},
language = {{eng}},
note = {{Student Paper}},
title = {{Autonomous Escort with an Unmanned Surface Vessel Using Model Predictive Control}},
year = {{2026}},
}