Path Planning for Autonomous Sailing Vessels: Developing Robust and Efficient Survey Strategies
Name
ahlers-mahlers-ne_ms-meche-2025-thesis.pdf
Description
Thesis PDF
Size
7.45 MB
Format
Adobe PDF
Checksum (MD5)
f29f309f1aa45e7fcd5232c2fe1fe96d
Author(s)
Ahlers, Matthew C.
Advisor(s)
Benjamin, Michael R.
Date Issued
May 2025
Publisher
Massachusetts Institute of Technology
Abstract
Autonomous sailing vessels offer a promising solution for maritime research, offering low maintenance and sustainable platforms for environmental monitoring and data collection. These vessels utilize wind power, eliminating the need for conventional fuel and enabling long-duration operations with minimal environmental impact. Their applications range from oceanographic studies to maritime surveillance, where persistent and autonomous data collection is essential. This thesis explores the challenges and methodologies associated with path planning for autonomous sailing, particularly in the context of survey operations. Unlike traditional motorized vessels, sailing autonomy must account for wind variability, sail dynamics, and limited maneuverability, requiring specialized path-planning techniques to ensure efficient and reliable navigation. The research investigates various sail and hull configurations, the dynamics of windpowered propulsion, and the application of autonomy frameworks such as MOOS-IvP. A key focus is on optimizing continuous coverage path planning (CPP) to maximize efficiency while adapting to environmental constraints. By integrating real-time wind data and vessel performance characteristics, the study refines survey strategies that enhance mission effectiveness. Different survey strategies are implemented and evaluated using both simulation and real-world testing on the Charles River. These trials demonstrate the feasibility of fixed-path decomposition approaches and adaptive moving horizon control methods, evaluating methods with the impact of wind conditions on autonomous sailing performance. The results contribute to the development of robust and efficient survey strategies that improve the autonomy and reliability of wind-powered marine vessels.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
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