DocumentCode :
1772998
Title :
An algorithm to identify docking locations for autonomous surface vessels from 3-D LiDAR scans
Author :
Esposito, Joel M. ; Graves, Mitchell
Author_Institution :
Syst. Eng. Dept., United States Naval Acad., Annapolis, MD, USA
fYear :
2014
fDate :
14-15 April 2014
Firstpage :
1
Lastpage :
6
Abstract :
In this paper we present a novel algorithm to identify docks (or piers) from Light Detection and Ranging (LiDAR) scans. The algorithm exploits the expected geometric features of the dock and does not require modifying the dock in any way. Our approach consists of a novel combination and application of open source tools for point cloud and image processing. In our limited testing on 8 fused data sets, the algorithm successfully identified a usable portion of all the docks with only one false positive (a seawall). The target application is automated docking (a.k.a. recovery) for small Unmanned Surface Vessels (USVs).
Keywords :
computer vision; marine vehicles; mobile robots; optical radar; public domain software; 3-D LiDAR scans; USV; automated docking; autonomous surface vessels; docking locations; expected geometric features; image processing; open source tools; point cloud; unmanned surface vessels; Data collection; Distance measurement; Google; Laser radar; Lasers; Three-dimensional displays; Vehicles; LiDAR; Object Recognition; Unmanned Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Technologies for Practical Robot Applications (TePRA), 2014 IEEE International Conference on
Conference_Location :
Woburn, MA
Print_ISBN :
978-1-4799-4606-8
Type :
conf
DOI :
10.1109/TePRA.2014.6869160
Filename :
6869160
Link To Document :
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