This paper presents a complete coverage path planning method, which combines local space coverage with global motion planning. It is realized by modeling mobile robot environment based on Boustrophedon cell decomposition method; and according to the characteristics of regional environment model, the connectivity of the traversing space is represented by a complete weighted connected matrix. Then Genetic algorithm (GA) is used to optimize the subspace traversal distance to obtain the shortest global traversal sequence of mobile robot.
Based on the Antibody Clonal Selection Theory of immunology, an adaptive dynamic clone select algorithm is put forward. The new algorithm is intended to integrate the local searching with the global and the probability evolution searching with the stochastic searching. Compared with other algorithms, the new algorithm prevents prematurely more effectively and has high convergence speed. Numeric experiments of function optimization indicate that the new algorithm is effective and useful.
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