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Paper WeC08.2

Douillard, Bertrand (University of Syndey), Quadros, Alastair James (The University of Sydney), Morton, Peter (University of Sydney), Underwood, James Patrick (The University of Sydney), De Deuge, Mark (The University of Sydney), Hugosson, Simon (Linköping University), Hallström, Manfred (Linköping University), Bailey, Tim (University of Sydney)

Scan Segments Matching for Pairwise 3D Alignment

Scheduled for presentation during the Regular Session "SLAM II" (WeC08), Wednesday, May 16, 2012, 14:45−15:00, Meeting Room 8 (Wacipi)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on November 18, 2017

Keywords Mapping, Range Sensing, Field Robots

Abstract

This paper presents a method for pairwise 3D alignment which solves data association by matching scan segments across scans. Generating accurate segment associations allows to run a modified version of the Iterative Closest Point (ICP) algorithm where the search for point-to-point correspondences is constrained to associated segments. The novelty of the proposed approach is in the segment matching process which takes into account the proximity of segments, their shape, and the consistency of their relative locations in each scan. Scan segmentation is here assumed to be given (recent studies provide various alternatives). The method is tested on seven sequences of Velodyne scans acquired in urban environments. Unlike various other standard versions of ICP, which fail to recover correct alignment when the displacement between scans increases, the proposed method is shown to be robust to displacements of several meters. In addition, it is shown to lead to savings in computational times which are potentially critical in real-time applications.

 

 

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