Efficient path planning algorithms for Unmanned Surface Vehicle

Files

Efficient_path_planning_algorithm_of_unmanned_surface_vehicle-2016.pdf (1.02 MB)

Date

2016-11-01

Authors

Niu, Hanlin
Lu, Yu
Savvaris, Al
Tsourdos, Antonios

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Department

Type

Conference paper

ISSN

2405-8963

Format

Free to read from

URI

http://dx.doi.org/10.1016/j.ifacol.2016.10.331
 https://dspace.lib.cranfield.ac.uk/handle/1826/11081

Citation

Niu H, Lu Y, Savvaris A, Tsourdos A, Efficient path planning algorithms for Unmanned Surface Vehicle, IFAC-PapersOnLine,Volume 49, Issue 23, 2016, Pages 121–126, 10th IFAC Conference on Control Applications in Marine SystemsCAMS 2016 — Trondheim, Norway, 13—16 September 2016.

Abstract

The C-Enduro Unmanned Surface Vehicle (USV) is designed to operate at sea for extended periods of time (up to 3 months). To increase the endurance capability of the USV, an energy efficient path planning algorithm is developed. The proposed path planning algorithm integrates the Voronoi diagram, Visibility algorithm, Dijkstra search algorithm and takes also into account the sea current data. Ten USV simulated mission scenarios at different time of day and start/end points were analysed. The proposed approach shows that the amount of energy saved can be up to 21%. Moreover, the proposed algorithm can be used to calculate a collision free and energy efficient path to keep the USV safe and improve the USV capability. The safety distance between the USV and the coastline can also be configured by the user.

Description

Software Description

Software Language

Github

Keywords

unmanned surface vehicles, collision avoidance, Voronoi diagram, Visibility graph, path planning

DOI

Rights

Attribution-Non-Commercial-No Derivatives 3.0 (CC BY-NC-ND 3.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Relationships

Relationships

Supplements

Funder/s

Collections

Staff publications (SATM)