A Path Planning Method for Mobile Robots Incorporating A* and Sparrow Search Algorithms

To address the problems of non-optimal path planning and unsmooth paths of mobile robots in complex environments, a path planning method for mobile robots that incorporates A* and sparrow search algorithm is proposed. Firstly, we propose an Improved Sparrow Search Algorithm (ISSA) that incorporates the improved logistic chaos mapping, adaptive dynamic weighting and alignment difference evolution strategy. Secondly, the concept of “A*-start/end line” secondary search region is introduced to the traditional A* algorithm. Finally, the improved sparrow search algorithm is combined with the A* algorithm to solve the problem of low search accuracy and non-optimal paths in the traditional A* algorithm by using its ability to help accelerate the iterative search, and also effectively reduce the problem of strong randomness of the sparrow search algorithm itself, so as to obtain a global path planning method with both optimality and stability. By comparing and verifying with other mobile robot path planning algorithms, the experimental results show that the improved algorithm proposed in the article has a better search effect and greater stability.