Planning feasible and safe paths online for autonomous underwater vehicles in unknown environments

Hernández, Juan David ORCID: https://orcid.org/0000-0002-9593-6789, Moll, Mark, Vidal, Eduard, Carreras, Marc and Kavraki, Lydia E. 2016. Planning feasible and safe paths online for autonomous underwater vehicles in unknown environments. Presented at: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, Korea, October 9-14 2016. 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). pp. 1313-1320. 10.1109/IROS.2016.7759217

Preview

PDF - Accepted Post-Print Version Download (3MB) | Preview

Abstract

We present a framework for planning collision-free and safe paths online for autonomous underwater vehicles (AUVs) in unknown environments. We build up on our previous work and propose an improved approach. While preserving its main modules (mapping, planning and mission handler), the framework now considers motion constraints to plan feasible paths, i.e., those that meet vehicle’s motion capabilities. The new framework also incorporates a risk function to avoid navigating close to nearby obstacles, and reuses the last best known solution to eliminate time-consuming pruning routines. To evaluate this approach, we use the Sparus II AUV, a torpedo-shaped vehicle performing autonomous missions in a 2-dimensional workspace. We validate the framework’s new features by solving tasks in both simulation and real-world in-water trials and comparing results with our previous approach.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Engineering
Additional Information:	"© 2016 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."
ISBN:	9781509037636
ISSN:	2153-0866
Date of First Compliant Deposit:	19 February 2021
Date of Acceptance:	1 July 2016
Last Modified:	09 Nov 2022 10:10
URI:	https://orca.cardiff.ac.uk/id/eprint/138536

Citation Data

Cited 37 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item