Path planning for multiple mobile robots under double-warehouse

•Path planning problems under double-warehouse are modeled scientifically.•Model characteristics are illustrated in detail.•Approach with improved PSO is proposed.•Approach fits for multi-robot paths planning under double-warehouse. This work investigates the conflict-free path planning problems for...

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Bibliographic Details
Published inInformation sciences Vol. 278; pp. 357 - 379
Main Authors Ma, Yong, Wang, Hongwei, Xie, Yong, Guo, Min
Format Journal Article
LanguageEnglish
Published Elsevier Inc 10.09.2014
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ISSN0020-0255
1872-6291
DOI10.1016/j.ins.2014.03.058

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Summary:•Path planning problems under double-warehouse are modeled scientifically.•Model characteristics are illustrated in detail.•Approach with improved PSO is proposed.•Approach fits for multi-robot paths planning under double-warehouse. This work investigates the conflict-free path planning problems for efficient guidance of multiple mobile robots under the dynamic double-warehouse environment, a challenging problem that appears recurrently in a wide range of applications such as the service robots moving in a multistory building. United with two symmetrical transfer elevators, double-warehouse consists of two parallel warehouses. Within each warehouse, the polynomial based paths are subject to constraints such as motion boundaries, kinematics constraints, obstacle-avoidance, limited resource of elevators and smoothness. We formulate the shortest path planning problems as one time-varying nonlinear programming problem (TNLPP) while restricted to the above constraints, and apply the multi-phase strategy to reduce their difficulty. We present the new variant algorithms of PSO named constriction factor and random perturb PSO (Con-Per-PSO) and the simulating annealing PSO (SA-PSO) to achieve the solution. Numerical simulations verify that, our approach can fulfill multiple mobile robots path planning problems under double-warehouse successfully.
ISSN:0020-0255
1872-6291
DOI:10.1016/j.ins.2014.03.058