Research on Intelligent Pick-Up Route Planning of a Logistics Cycle Automatic Robot

Abstract

In order to improve the efficiency of a logistics cycle robot picking up goods, a path planning algorithm based on artificial intelligence was proposed. After analyzing the particle swarm optimization algorithm, the particle swarm optimization algorithm is optimized and improved and the path planning of a single robot is obtained. On this basis, a multipopulation particle swarm optimization (CMMPPSO) algorithm is proposed. The results show that the JMPOPSO algorithm is more accurate than the BPSO algorithm and the maximum fitness optimized by the BPSO algorithm is 1.59, while the maximum fitness optimized by the JMPOPSO algorithm is 1.98. The path optimized by the CMMPPSO algorithm based on JMPOPSO is better than that optimized by the CMMPPSO algorithm based on BPSO, shortening by about 25% and shortening the time by about 30. Simulation experiments verify the effectiveness of the CMMPPSO algorithm.