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Convergence-guaranteed time-varying RRT path planning for profiling floats in 4-dimensional flow

conference contribution
posted on 2014-01-01, 00:00 authored by Van Thanh HuynhVan Thanh Huynh, M Dunbabin, R Smith
This paper presents an extension to the
Rapidly-exploring Random Tree (RRT) al-
gorithm applied to drifting autonomous un-
derwater vehicles. The proposed algorithm
is able to plan paths that guarantee con-
vergence in the presence of time-varying
ocean dynamics. The method utilizes 4-
Dimensional ocean model prediction data as
an evolving basis for expanding the tree from
the start location to the goal. The perfor-
mance of the proposed method is validated
through Monte-Carlo simulations. Results
illustrate the importance of the temporal
variance in path execution and demonstrate
the convergence performance of the proposed
methods.

History

Event

Australian Robotics & Automation Association. Conference (2014 : Melbourne, Vic.)

Series

Australian Robotics & Automation Association Conference

Pagination

1 - 9

Publisher

Australian Robotics and Automation Association

Location

Melbourne, Vic.

Place of publication

Sydney, N.S.W.

Start date

2014-12-02

End date

2014-12-04

ISSN

1448-2053

ISBN-13

9780980740455

Language

eng

Publication classification

E Conference publication; E1.1 Full written paper - refereed

Copyright notice

[2014, ARAA]

Editor/Contributor(s)

[Unknown]

Title of proceedings

ACRA 2014 : Proceedings of the Australasian Conference on Robotics and Automation 2014