A Bi-Level Probabilistic Path Planning Algorithm for Multiple Robots with Motion Uncertainty

Jingchuan Wang, Ruochen Tai and Jingwen Xu

Complexity, 2020, vol. 2020, 1-16

Abstract:

For improving the system efficiency when there are motion uncertainties among robots in the warehouse environment, this paper proposes a bi-level probabilistic path planning algorithm. In the proposed algorithm, the map is partitioned into multiple interconnected districts and the architecture of proposed algorithm is composed of topology level and route level generating from above map: in the topology level, the order of passing districts is planned combined with the district crowdedness to achieve the district equilibrium and reduce the influence of robots under motion uncertainty. And in the route level, a MDP method combined with probability of motion uncertainty is proposed to plan path for all robots in each district separately. At the same time, the number of steps for each planning is dependent on the probability to decrease the number of planning. The conflict avoidance is proved, and optimization is discussed for the proposed algorithm. Simulation results show that the proposed algorithm achieves improved system efficiency and also has acceptable real-time performance.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:9207324

DOI: 10.1155/2020/9207324

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