Path Planning for Multi-AGV Systems based on Two-Stage Scheduling

doi:10.23940/ijpe.17.08.p16.13471357

Abstract

Abstract: This paper proposes an optimal path planning method for the multiple automated guided vehicle (AGV) system based on two-staged scheduling; at the offline scheduling stage, high degree of genetic algorithm is used for the optimal obstacle avoidance path planning of AGV under the static environment, which cannot only solve the premature convergence of genetic algorithm, but also the obstacle avoidance of AGV path planning. Online scheduling stage mainly refers to test the node conflict, opposite conflict and pursuit conflict between AGV and these conflicts are solved to achieve online collision avoidance scheduling for AGV. Finally, the paper uses the secondary developed openTCS for algorithm simulation. The processing methods when all kinds of conflicts occur are simulated in the multi-AGV systems, and the results show that the method is effective and reliable for the path planning of multi-AGV systems.

Submitted on October 11, 2017; Revised on November 12, 2017; Accepted on November 23, 2017
References: 15

Wan Xu, Qi Wang, Mingjin Yu, and Daxing Zhao. Path Planning for Multi-AGV Systems based on Two-Stage Scheduling [J]. Int J Performability Eng, 2017, 13(8): 1347-1357.

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References 0

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