Autonomous Docking of an Unmanned Surface Vehicle using Model Predictive Control
(2022)Department of Automatic Control
- Abstract
- Autonomous docking of marine vessels presents challenges different from the ones faced when travelling at open sea or in an archipelago. External disturbances due to the varying environment and accurate positioning at low speed are examples of these kinds of challenges. The aim of this work has been to develop and implement an autopilot algorithm for docking. This was to be done for a specific marine vessel, using model predictive control (MPC). The vessel in question was Saab Kockums’ Piraya, an unmanned surface vehicle (USV).
The problem formulation includes design and implementation of the MPC itself, as well as handling external disturbances and obstacle avoidance. Different software approaches to solving the optimization problem... (More) - Autonomous docking of marine vessels presents challenges different from the ones faced when travelling at open sea or in an archipelago. External disturbances due to the varying environment and accurate positioning at low speed are examples of these kinds of challenges. The aim of this work has been to develop and implement an autopilot algorithm for docking. This was to be done for a specific marine vessel, using model predictive control (MPC). The vessel in question was Saab Kockums’ Piraya, an unmanned surface vehicle (USV).
The problem formulation includes design and implementation of the MPC itself, as well as handling external disturbances and obstacle avoidance. Different software approaches to solving the optimization problem have been explored, as well as different solutions to the matter of advancing towards the desired position. Three approaches were implemented in an MPC framework.
The developed controllers have been successfully tested in simulations, in experiments using a small-scale model car dynamically representing the USV, as well as on the USV at Gränsö, Västervik. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9096721
- author
- Kockum, Sofia
- supervisor
- organization
- year
- 2022
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6164
- ISSN
- 0280-5316
- language
- English
- id
- 9096721
- date added to LUP
- 2022-08-12 09:50:13
- date last changed
- 2022-08-12 09:50:13
@misc{9096721,
abstract = {{Autonomous docking of marine vessels presents challenges different from the ones faced when travelling at open sea or in an archipelago. External disturbances due to the varying environment and accurate positioning at low speed are examples of these kinds of challenges. The aim of this work has been to develop and implement an autopilot algorithm for docking. This was to be done for a specific marine vessel, using model predictive control (MPC). The vessel in question was Saab Kockums’ Piraya, an unmanned surface vehicle (USV).
The problem formulation includes design and implementation of the MPC itself, as well as handling external disturbances and obstacle avoidance. Different software approaches to solving the optimization problem have been explored, as well as different solutions to the matter of advancing towards the desired position. Three approaches were implemented in an MPC framework.
The developed controllers have been successfully tested in simulations, in experiments using a small-scale model car dynamically representing the USV, as well as on the USV at Gränsö, Västervik.}},
author = {{Kockum, Sofia}},
issn = {{0280-5316}},
language = {{eng}},
note = {{Student Paper}},
title = {{Autonomous Docking of an Unmanned Surface Vehicle using Model Predictive Control}},
year = {{2022}},
}