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RRT∗ Trajectory Scheduling Using Angles-Only Measurements for AUV Recovery

conference contribution
posted on 2024-11-03, 13:32 authored by Xuezhi WangXuezhi Wang, Simon Williams, Daniel Angley, Christopher Gilliam, Trevor Jackson, Richard Ellem, Amanda Bessell, Bill Moran
Sensor trajectory optimisation involves extensive search over the sensor motion space against an optimisation criterion. The search under dynamic programming or fixed grid is often computationally nontrivial even for a myopic search scenario. In this paper, we study the problem of an autonomous underwater vehicle planning its return route to a moving recovery vessel. To complicate the issue, the AUV needs to localize the vessel using angle-only measurements. Accordingly, we propose a random sampling based trajectory planning algorithm that incorporates both a dynamic goal and the need to localize that goal. More precisely, we incorporate an information theoretic cost into a rapid-exploring random tree trajectory planning framework thus allowing the AUV to both localize and reach the recovery vessel. Our experimental results show that the proposed method may achieve the same trajectory optimisation performance as that under dynamic programming method but with greater computational efficiency.

History

Number

9011175

Start page

1

End page

6

Total pages

6

Outlet

Proceedings of the 22nd International Conference on Information Fusion (FUSION 2019)

Name of conference

FUSION 2019

Publisher

IEEE

Place published

United States

Start date

2019-07-02

End date

2019-07-05

Language

English

Copyright

© 2019 ISIF-International Society of Information Fusion.

Former Identifier

2006106450

Esploro creation date

2021-08-11

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