APR - Global Scan Matching Using Anchor Point Relationships

Global self-localization, i.e. the ability to generate position estimates without initial hypotheses, decisively improves robustness of mobile robot localiza- tion since it allows recovery from arbitrary position errors. APR is a pattern match- ing algorithm designed for the realtime search of best matching laser scans in a set of given reference scans. The algorithm's output is a number of weighted hypothe- ses which makes APR especially attractive for probabilistic techniques aiming at global localization capabilities. The concept of reference scans makes APR appli- cable in both, topological and metric-map navigation schemes. Experimental re- sults are presented for the matching of 180° laser scans in an office environment.

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