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A novel multi-objective artificial bee colony algorithm for multi-robot path planning

Zhongya Wang, Min Li, Lianhang Dou, Yang Li, Qingying Zhao, Jie Li

Year
2015
Citations
20

Abstract

An improved multi-objective artificial bee colony algorithm is designed in this paper reflecting the multi-objective characteristic of multi-robot path planning problems. Firstly, the foraging mechanism is optimized and a new method to calculate crowding distance is proposed. The restructuring and elimination mechanism of food sources are also presented. Secondly, an improved environment map representation method is presented in which the path information of robots is denoted using Cartesian coordinates directly. Thirdly, three objective functions for path planning are designed according to three key performance indicators which are length, safety and smoothness of the path. Finally, the simulation results show that the improved multi-objective artificial bee colony algorithm can be effectively applied to solve multi-robot path planning problems.

Keywords

Motion planningRobotArtificial bee colony algorithmPath (computing)Computer scienceSmoothnessMathematical optimizationAny-angle path planningKey (lock)Algorithm

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