| [85628] |
| Title: Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats. <em>Robotic Sailing, Proceedings of the 5th International Robotic Sailing Conference</em> |
| Written by: L. Hertel and A. Schlaefer |
| in: <em>Robotic Sailing 2012</em>. (2012). |
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| on pages: 37-48 |
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| Organization: Robotic Sailing, Proceedings of the 5th International Robotic Sailing Conference |
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| DOI: 10.1007/978-3-642-33084-1_4 |
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Abstract: Finding the optimal parameter settings to control a sailing robot is an intricate task, as sailing presents a fairly complex problem with a highly non-linear interaction of boat, wind, and water. As no complete mathematical model for sailing is available, we studied how a large set of sensor data gathered in different conditions can be used to obtain parameters. In total, we analyzed approximately 2 million records collected during more than 110 hours of autonomous sailing on 55 different days. The data was preprocessed and episodes of stable sailing were extracted before studying boat, sail and rudder trim with respect to speed, course stability, and energy consumption. Our results highlight the multi-criteria nature of optimizing robotic sailboat control and indicate that a reduced set of preferable parameter settings may be used for effective control.