sis 18: e10

Research Article

A novel A* method fusing bio-inspired algorithm for mobile robot path planning

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  • @ARTICLE{10.4108/eai.14-9-2021.170953,
        author={Yang Sun and Haipeng Wang},
        title={A novel A* method fusing bio-inspired algorithm for  mobile robot path planning},
        journal={EAI Endorsed Transactions on Scalable Information Systems: Online First},
        keywords={mobile robot path planning, A* algorithm, pigeon algorithm, ant colony algorithm, B-spline curve},
  • Yang Sun
    Haipeng Wang
    Year: 2021
    A novel A* method fusing bio-inspired algorithm for mobile robot path planning
    DOI: 10.4108/eai.14-9-2021.170953
Yang Sun1,*, Haipeng Wang2
  • 1: Software College, Shenyang Normal University, Shenyang 110034, China
  • 2: SIASUN Robot & Automation CO.,Ltd.
*Contact email:


The path planning of mobile robot is to find an optimal collision-free path in time distance or space from the starting point to the target point in a given environment. With the popularization and application of mobile robots, if the efficiency of mobile robots path is not high, the working quality will be seriously affected. How to quickly plan an effective safe path is of great research significance and practical application value. Therefore, we propose a novel A* algorithm based on Bio-inspired algorithm for mobile robot path planning. Firstly, the synchronous bidirectional A* algorithm is used to optimize the pheromone of ant colony algorithm, and the transition probability and pheromone update mechanism of ant colony algorithm are improved, so that the global optimization speed of the algorithm is faster and the path length of mobile robot is shortened. Furthermore, the static path is used to initialize the pigeon algorithm. Then, the improved pigeon algorithm is utilized to plan the local path of the mobile robot, and the simulated annealing criterion is introduced to solve the local optimal problem. The logarithmic S-type transfer function is adopted to optimize the step size of the pigeon number, so that the collision with the dynamic obstacles can be better avoided. Finally, a modified B-spline curve is used to smooth
and re-plan the path. The simulation results show that the proposed method can realize path planning more effectively in complex dynamic environment.