• Electronics Optics & Control
  • Vol. 29, Issue 11, 118 (2022)
LI Zhikun1、2 and ZHAO Qiannan2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2022.11.021 Cite this Article
    LI Zhikun, ZHAO Qiannan. Path Planning of Mobile Robot Based on Artificial Potential Field and Ant Colony Algorithm[J]. Electronics Optics & Control, 2022, 29(11): 118 Copy Citation Text show less

    Abstract

    By combining the artificial potential field method with ant colony algorithm,a path planning method of mobile robot based on artificial potential field and ant colony algorithm is presented.On the one hand,the influence factor of target point distance is introduced to improve the influence of potential field force on mobile robot path search.By improving the repulsion field function,the mobile robot is prevented from being unable to plan the optimal path due to large repulsion.On the other hand,constructing the potential field force heuristic function,taking into account the distance heuristic information and the potential field heuristic information at the same time,initializing the differential allocation of pheromones is conducive to improving the convergence speed of the algorithm.The experimental results show that compared with that of the algorithm in Reference [15],the optimal path length,the number of path turns and the convergence speed of the proposed algorithm has been improved by 2.6%,25% and 66.7% respectively,which shows the superiority of the algorithm in path planning.
    LI Zhikun, ZHAO Qiannan. Path Planning of Mobile Robot Based on Artificial Potential Field and Ant Colony Algorithm[J]. Electronics Optics & Control, 2022, 29(11): 118
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