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


Autoria(s): Ngo, Phillip; Al-Sabban, Wesam H.; Thomas, Jesse; Anderson, Will; Das, Jnashewar; Smith, Ryan N.
Contribuinte(s)

Katupitiya, Jayantha

Guivant, Jose

Eaton, Ray

Data(s)

2013

Resumo

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.

Identificador

http://eprints.qut.edu.au/66638/

Publicador

Australian Robotics & Automation Association

Relação

http://www.araa.asn.au/acra/acra2013/papers/pap151s1-file1.pdf

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.

Direitos

Copyright 2013 [please consult the authors]

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #Robotic path planning #Predictive kinematic model #Autonomous surface vehicle
Tipo

Conference Paper