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The Iterative Closest Point (ICP) algorithm is to align for the two point sets, which is widely used in map building of an uncertain environment. However, the original ICP algorithm is easily affected by noise and discrete points, making the error of alignment very large. At the same time, in a row scanning by the Laser Range Finder (LRF), the more data points accumulate, the larger the errors of...
This paper proposes the use of Particle Swarm Optimization (PSO) to work with an Enhanced-ICP to effectively filter out outliers and avoid false matching points during the map building of an unknown environment, where PSO is used to solve the local optima problem to obtain better transformation results for two data sets with excessive difference in initial position and direction. Then, we use part...
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