陈果, 何代钰, 欧阳博, 颜志, 文蔚, 饶有福, 王耀南. 基于链状结构保持的多AGV系统灵活高效死锁避免控制策略[J]. 机器人, 2023, 45(5): 591-602. DOI: 10.13973/j.cnki.robot.220352
引用本文: 陈果, 何代钰, 欧阳博, 颜志, 文蔚, 饶有福, 王耀南. 基于链状结构保持的多AGV系统灵活高效死锁避免控制策略[J]. 机器人, 2023, 45(5): 591-602. DOI: 10.13973/j.cnki.robot.220352
CHEN Guo, HE Daiyu, OUYANG Bo, YAN Zhi, WEN Wei, RAO Youfu, WANG Yaonan. Flexible and Efficient Deadlock Avoidance Control Strategy for multi-AGV Systems Based on Chain Structure Preservation[J]. ROBOT, 2023, 45(5): 591-602. DOI: 10.13973/j.cnki.robot.220352
Citation: CHEN Guo, HE Daiyu, OUYANG Bo, YAN Zhi, WEN Wei, RAO Youfu, WANG Yaonan. Flexible and Efficient Deadlock Avoidance Control Strategy for multi-AGV Systems Based on Chain Structure Preservation[J]. ROBOT, 2023, 45(5): 591-602. DOI: 10.13973/j.cnki.robot.220352

基于链状结构保持的多AGV系统灵活高效死锁避免控制策略

Flexible and Efficient Deadlock Avoidance Control Strategy for multi-AGV Systems Based on Chain Structure Preservation

  • 摘要: 现有的多AGV(自动导引车)系统处理死锁的方案往往约束过强, 压缩了潜在的性能优化空间。本文提出一种高度灵活的死锁避免算法, 通过分析系统状态图中的宏环结构并结合银行家算法来实现状态图的链状结构判断, 在确保算法高效性(最坏情形时间复杂度为O((|V|+|E|)|A|), 其中VEA分别代表节点、边、AGV)的同时, 实现了灵活的死锁避免。通过离散事件系统仿真及实际系统应用验证了算法的有效性, 结果表明, 在典型路线图上, 该算法相较于经典的银行家算法及其变种, 容许覆盖率提升高于16%, 在使用相同任务分配、路径规划算法的情况下, 任务平均完成时间降低了15%, 具有更高的灵活性, 有效提升了系统性能优化的潜力。

     

    Abstract: The existing deadlock handling methods for multi-AGV (automated guided vehicle) system are often too restrictive, which compresses the potential performance optimization space. This paper proposes a highly flexible deadlock avoidance algorithm to judge the chain structure of the state diagram based on the banker algorithm by analyzing the macro ring structure in the system state diagram, and implement flexible deadlock avoidance while ensuring the algorithm efficiency (the time complexity of the algorithm is O((|V|+|E|)|A|) in the worst case, where V, E, and A represent nodes, edges, and AGVs, respectively). The effectiveness of the proposed algorithm is verified by discrete event system simulation and practical system application. The results show that compared with the classical banker algorithm and its variants, the proposed algorithm can improve the allowable state space by more than 16% on typical road map, and the average task completion time is reduced by 15% when using the same task allocation and path planning algorithms. It demonstrates higher flexibility and effectively improves the potential of system performance optimization.

     

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