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Guide Circle-based Improved Ant Colony Algorithm

Chen Huang, Zhengzhong Gao, Junjun Chen, Luyao Zhou, Zhanming Lu, Qifei Qu

Year
2020
Citations
3

Abstract

Abstract In order to solve the path planning problem of autonomous mobile robots in an unknown environment, the traditional ant colony algorithm and the guide circle algorithm were combined, and an improved ant colony algorithm based on the guide circle was proposed. In terms of local path planning, the guide circle algorithm is used to avoid obstacles, which effectively solved the problem of unstable path planning ability in narrow spaces. In the aspect of global path planning, the concept of safety index circle is introduced according to the length between robot and obstacle, and partial heuristic information of ant colony algorithm is improved, so as to avoid the traditional ant colony algorithm falling into local optimal. It is verified by simulation experiments that the improved algorithm has a stronger global search capability, faster convergence speed, and enhanced path planning capability.

Keywords

Ant colony optimization algorithmsMotion planningComputer sciencePath (computing)AlgorithmConvergence (economics)Mathematical optimizationObstacleHeuristicMobile robot

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