A HYBRID GENETIC TABU SEARCH ALGORITHM FOR MOBILE ROBOT TO SOLVE AS/RS PATH PLANNING

Lei Wang and Chaomin Luo

Keywords

Path planning, genetic algorithm, mobile robot, dual command, tabu search, local navigation

Abstract

A two-stage path planning and real-time path trajectory control for mobile robot (MR) of automated storage retrieval system (AS/RS) are proposed. In the first stage, a hybrid algorithm (called genetic algorithm and tabu search (GATS)) combining tabu search (TS) with genetic algorithm (GA) is proposed to optimize the theoretical operating time. The reason behind using such a GATS is to combine the intensified local search capabilities and diversified global search of TS and GA respectively. In addition, the GATS achieves by using several small but important characteristics such as effective genetic operators, powerful chromosome representation, restricted neighbourhood strategies, and efficient search strategies along with initial innovative solutions. The GATS was compared with the pure GA and the pure TS. The theoretical simulation results for path planning problems of AS/RS indicate that the hybrid GATS is better than either pure GA or pure TS. The results of our research can well provide a method to manage and control MR of AS/RS. In the second stage, the light detection and ranging-based (LDARbased) local navigation method is used to control real-time path trajectory. Real-time simulation results indicate that an autonomous MR can control successfully its path trajectory in real time by using concurrent navigation and map building in unpredictable or dynamic environments.

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