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Improved Genetic Algorithm for Ground Robot's Path Planning with Aerial Vision

Jian Qiang Li, Hai Long Pei, Yu Xi Wang, Zhong Ming

Abstract


For the deficiency of ground robot in map building and path planning, this paper proposes a method based on the aerial robot vision. By aerial visual image, obstacle identification and ground environment building are studied. Obstacles information is effectively extracted by color threshold segmentation, regional connectivity, feature extraction and target recognition, and the map is constructed. Then this paper proposes an improved genetic algorithm for path planning based on the basic architecture of the obstacles on the ground map information. Finally experimental simulation is given for the proposed method, and achieved good result.

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DOI: http://dx.doi.org/10.21535%2FProICIUS.2014.v10.264

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