APR - Global Scan Matching Using Anchor Point Relationships

The 6th International Conference on Intelligent Autonomous Systems (IAS-6)
Venice, Italy, July 25-27, 2000

Joachim Weber, Klaus-Werner Jörg, Ewald von Puttkamer

Global self-localization, i.e. the ability to generate position estimates without initial hypotheses, decisively improves robustness of mobile robot localization since it allows recovery from arbitrary position errors. APR is a pattern matching 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 hypotheses which makes APR especially attractive for probabilistic techniques aiming at global localization capabilities. The concept of reference scans makes APR applicable in both, topological and metric-map navigation schemes. Experimental results are presented for the matching of 180° laser scans in an office environment.

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