Paper Info
Title
Improving 3D scan matching time of the coarse binary cubes method with fast spatial subsampling
Abstract
Exploiting the huge amount of real time range data provided by new multi-beam three-dimensional (3D) laser scanners is challenging for vehicle and mobile robot applications. The Coarse Binary Cube (CBC) method was proposed to achieve fast and accurate scene registration by maximizing the number of coincident cubes between a pair of scans. The aim of this paper is speeding up CBC with a fast spatial subsampling strategy for raw point clouds that employs the same type of efficient data structures as CBC. Experimental results have been obtained with the Velodyne HDL-32E sensor mounted on the Quadriga mobile robot on irregular terrain. The influence of the subsampling rate has been analyzed. Preliminary results show a relevant gain in computation time without losing matching accuracy.
Year
DOI
Venue
2013
10.1109/IECON.2013.6699804
Vienna
Keywords
Field
DocType
image matching,mobile robots,optical scanners,robot vision,sampling methods,3d scan matching time,cbc,velodyne hdl-32e sensor,coarse binary cubes method,coincident cubes,computation time,fast spatial subsampling strategy,irregular terrain,matching accuracy,mobile robot applications,multibeam three-dimensional laser scanners,quadriga mobile robot,raw point clouds,real time range data,vehicle applications
Data structure,Computer vision,Computer science,Terrain,Artificial intelligence,Point cloud,Mobile robot,Coincident,Cube,Binary number,Computation
Conference
ISSN
Citations 
PageRank 
1553-572X
1
0.36
References 
Authors
16
6
Name
Order
Citations
PageRank
Jesús Morales117916.38
Jorge Martínez29517.02
Anthony Mandow314813.28
Antonio J. Reina4354.47
Javier Serón5343.60
Alfonso García-cerezo622634.73