Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats

Lars Hertel; Alexander Schlaefer

doi:10.1007/978-3-642-33084-1_4

Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats

Lars Hertel, Alexander Schlaefer

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.

Original language	English
Title of host publication	Robotic Sailing 2012
Editors	Colin Sauzé, James Finnis
Number of pages	12
Place of Publication	Berlin, Heidelberg
Publisher	Springer Berlin Heidelberg
Publication date	2012
Pages	37-48
ISBN (Print)	978-3-642-33083-4
ISBN (Electronic)	978-3-642-33084-1
DOIs	https://doi.org/10.1007/978-3-642-33084-1_4
Publication status	Published - 2012
Event	The 5th World Robotic Sailing Championships and International Robotic Sailing Conference - Cardiff, United Kingdom Duration: 17.09.2012 → 21.09.2012

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SDG 3 Good Health and Well-being
SDG 7 Affordable and Clean Energy
SDG 9 Industry, Innovation, and Infrastructure

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10.1007/978-3-642-33084-1_4

Cite this

@inproceedings{9af913091f384798bf3f70048e45e968,

title = "Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats",

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.",

author = "Lars Hertel and Alexander Schlaefer",

year = "2012",

doi = "10.1007/978-3-642-33084-1\_4",

language = "English",

isbn = "978-3-642-33083-4",

pages = "37--48",

editor = "Colin Sauz{\'e} and James Finnis",

booktitle = "Robotic Sailing 2012",

publisher = "Springer Berlin Heidelberg",

note = "The 5th World Robotic Sailing Championships and International Robotic Sailing Conference, WRSC/IRSC 2012 ; Conference date: 17-09-2012 Through 21-09-2012",

}

Hertel, L & Schlaefer, A 2012, Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats. in C Sauzé & J Finnis (eds), Robotic Sailing 2012. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 37-48, The 5th World Robotic Sailing Championships and International Robotic Sailing Conference, Cardiff, United Kingdom, 17.09.12. https://doi.org/10.1007/978-3-642-33084-1_4

TY - GEN

T1 - Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats

AU - Hertel, Lars

AU - Schlaefer, Alexander

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - https://link.springer.com/chapter/10.1007/978-3-642-33084-1_4

U2 - 10.1007/978-3-642-33084-1_4

DO - 10.1007/978-3-642-33084-1_4

M3 - Conference contribution

SN - 978-3-642-33083-4

SP - 37

EP - 48

BT - Robotic Sailing 2012

A2 - Sauzé, Colin

A2 - Finnis, James

PB - Springer Berlin Heidelberg

CY - Berlin, Heidelberg

T2 - The 5th World Robotic Sailing Championships and International Robotic Sailing Conference

Y2 - 17 September 2012 through 21 September 2012

ER -

Data Mining for Optimal Sail and Rudder Control of Small Robotic Sailboats

Abstract

UN SDGs

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