Dynamic Target Driven Trajectory Planning using RRT

Simon Williams, Xuezhi Wang, Daniel Angley, Christopher Gilliam, Bill Moran, Richard Ellem, Trevor Jackson, Amanda Bessell

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we focus on dynamic trajectory planning for an autonomous underwater vehicle (AUV). Specifically, we are interested in planning the trajectory of an AUV as it returns to a moving recovery vessel. To aid in this task, the AUV is equipped with a passive, angle-only, sensor to enable localization of the recovery vessel. Accordingly, we present an algorithm that is capable of dynamically updating the trajectory of the AUV given measurement data from the passive sensor. Our approach is based on adapting a static trajectory planning algorithm from robotics, known as Rapidly-exploring Random Tree (RRT∗), to allow for localization and tracking of a dynamic target (i.e. the recovery vessel). In contrast to dynamic programming or fixed grid trajectory planning, the RRT∗ offers a computationally efficient method for long-term trajectory planning with probabilistic guarantees of optimality. In this framework, we explore two options: trajectory planning based on minimising the distance to the target; and trajectory planning based on maximising the tracking accuracy of the target using an information theoretic cost. Using AUV recovery as an evaluation scenario, we analyse and evaluate the proposed trajectory planning algorithm against traditional dynamic programming methods. In particular, we consider trajectory planning in noisy and obstructed environments.

Original languageEnglish
Title of host publicationFUSION 2019 - 22nd International Conference on Information Fusion
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9780996452786
Publication statusPublished - Jul 2019
Event22nd International Conference on Information Fusion, FUSION 2019 - Ottawa, Canada
Duration: 2 Jul 20195 Jul 2019

Publication series

NameFUSION 2019 - 22nd International Conference on Information Fusion

Conference

Conference22nd International Conference on Information Fusion, FUSION 2019
Country/TerritoryCanada
CityOttawa
Period2/07/195/07/19

Bibliographical note

Funding Information:
This research is supported by DST Group under the research agreement “Trajectory Optimisation for a Moving Observer with 3-D Angle Only Sensor Measurements”.

Publisher Copyright:
© 2019 ISIF-International Society of Information Fusion.

Keywords

  • autonomous underwater vehicle recovery
  • passive target tracking
  • path planning
  • RRT
  • Trajectory optimisation

ASJC Scopus subject areas

  • Information Systems
  • Instrumentation

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