Fast Genetic Scan Matching Using Corresponding Point Measurements in Mobile Robotics

Authors:
Kristijan Lenac;Enzo Mumolo;Massimiliano Nolich
Affiliations:
DEEI, University of Trieste, Via Valerio 10, Trieste, Italy and AIBS Lab, Via del Follatoio 12, Trieste, Italy;DEEI, University of Trieste, Via Valerio 10, Trieste, Italy;DEEI, University of Trieste, Via Valerio 10, Trieste, Italy
Venue:
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Year:
2009

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Abstract

In this paper we address the problem of aligning two partially overlapping surfaces represented by points obtained in subsequent 2D scans for mobile robot pose estimation. The measured points representation contains incomplete measurements. We solve this problem by minimizing an alignment error via a genetic algorithm. Moreover, we propose an alignment metric based on a look-up table built during the first scan. Experimental results related to the convergence of the proposed algorithm are reported. We compare our approach with other scan matching algorithms proposed in the literature, and we show that our approach is faster and more accurate than the others.