An analysis of regression models for predicting the speed of a wave glider autonomous surface vehicle

Ngo, Phillip, Al-Sabban, Wesam H., Thomas, Jesse, Anderson, Will, Das, Jnashewar, & Smith, Ryan N. (2013) An analysis of regression models for predicting the speed of a wave glider autonomous surface vehicle. In Katupitiya, Jayantha, Guivant, Jose, & Eaton, Ray (Eds.) Proceedings of the 2013 Australasian Conference on Robotics & Automation, Australian Robotics & Automation Association, University of New South Wales, Sydney, NSW, pp. 1-10.

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An important aspect of robotic path planning for is ensuring that the vehicle is in the best location to collect the data necessary for the problem at hand. Given that features of interest are dynamic and move with oceanic currents, vehicle speed is an important factor in any planning exercises to ensure vehicles are at the right place at the right time. Here, we examine different Gaussian process models to find a suitable predictive kinematic model that enable the speed of an underactuated, autonomous surface vehicle to be accurately predicted given a set of input environmental parameters.

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3 citations in Scopus
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ID Code: 66638
Item Type: Conference Paper
Refereed: Yes
Keywords: Robotic path planning, Predictive kinematic model, Autonomous surface vehicle
ISBN: 9780980740448
ISSN: 1448-2053
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2013 [please consult the authors]
Deposited On: 28 Jan 2014 03:33
Last Modified: 30 Jan 2014 05:51

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