Hernández, Juan David ![]() ![]() |
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Abstract
We present a framework for planning collision-free paths online for autonomous underwater vehicles (AUVs) in unknown environments. It is composed of three main modules (mapping, planning and mission handler) that incrementally explore the environment while solving start-to-goal queries. We use an octree-based representation of the environment and we extend the optimal rapidly-exploring random tree (RRT*) using concepts of anytime algorithms and lazy collision evaluation, thus including the capability to replan paths according to nearby obstacles perceived during the execution of the mission. To validate our approach, we plan paths for the SPARUS-II AUV, a torpedo-shaped vehicle performing autonomous missions in a 2-dimensional workspace. We demonstrate its feasibility with the SPARUS-II AUV in both simulation and real-world in-water trials.
Item Type: | Conference or Workshop Item (Paper) |
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Date Type: | Published Online |
Status: | Published |
Schools: | Engineering |
Additional Information: | "© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works." |
Publisher: | IEEE |
ISBN: | 9781479969234 |
ISSN: | 1050-4729 |
Date of First Compliant Deposit: | 31 March 2021 |
Date of Acceptance: | 30 January 2015 |
Last Modified: | 09 Nov 2022 10:24 |
URI: | https://orca.cardiff.ac.uk/id/eprint/139362 |
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