A Grid-Based Monte Carlo Localization with Hierarchical Free-Form Scan Matching
This paper is concerned with the localization problem of robot in unstable environment. To improve the accuracy of the localization result in the environment, a grid-based Monte Carlo localization algorithm with hierarchical free-form scan matching (MCL-HF) is proposed. In MCL-HF algorithm the distribution of the samples is adapted by the most recent observation. To simplify the process of the adaptation a feature-based scan-matching algorithm is adopted in the grid-based localization algorithm in a hierarchical free-form. The advantage of the proposed algorithm is demonstrated through the experiment results.
KeywordsLocalization Particle filter Scan-matching
This work is partially supported by National Key Research and Development Program of China under Grant 2017YFF0205306, National Nature Science Foundation of China under Grant 91648117, and Beijing Natural Science Foundation under Grant 4172055.
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