Research on the global path planning of the storage robot based on the improved Harris Hawks optimization algorithm
The purpose of this study is to explore the global path planning of warehouse robots based on the improved Harris Eagle optimization algorithm,in order to improve the navigation efficiency of robots in the storage environment.By introducing Tent chaos mapping,escape star regulation mechanism and Cauchy anti-learning variation strategy,the researchers improved the tradi-tional Harris Hawks optimization algorithm,so as to improve the search ability and global optimization performance of the algo-rithm.On the basis of proposing the improved TCLHHO algorithm,the researchers comprehensively evaluated the performance of the improved algorithm through the standard test function,compared the advantages and disadvantages with the traditional algo-rithm,and applied the improved algorithm for the storage robot path planning in the simulation environment.The study shows that the improved TCLHHO algorithm shows better convergence and higher path quality in the path planning,which significantly im-proves the planning efficiency compared to the traditional algorithm.This research not only provides an effective optimization tool for the path planning of warehouse robots,but also promotes the technological progress of intelligent logistics system,which is of im-portant practical significance for practical application.
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