Fusion of Improved A* Algorithm and Optimal Dynamic Window Approach for Mobile Robot Path Planning

Aiming at global path planning of mobile robot in unknown environment and how to avoid random dynamic and static obstacles in unknown environment, A path planning algorithm combining improved A* algorithm and optimized dynamic window method is proposed. The A* algorithm has a more comprehensive global path planning ability, and has a good computational speed, but also is currently the most widely used algorithm for global path planning. But the traditional A* algorithm also has many drawbacks, low search efficiency in complex environments, the existence of a large number of redundant nodes, the path is not smooth and other problems. Therefore, this paper proposes an improved A* algorithm first, which reduces the search direction, removes redundant turning points and covariance nodes, and obtains a smooth optimal planning path after Bessel curve optimization; secondly, it is optimized for the single motion state of the dynamic window method, and the safety distance is set to cope with obstacles that have a similar motion state to the robot, and the improved A* algorithm is integrated with the optimized dynamic window method, so as to meet the global planning The improved A* algorithm is integrated with the optimized dynamic window method, so as to realize obstacle avoidance in the face of random obstacles at the local position while satisfying the optimal curve in the global planning path. After simulation experiments with the traditional A* algorithm in several groups of different environments, the experimental results are obtained, the improved A* algorithm has obvious advantages in global path planning, the computation time is reduced by 40%, the search nodes are reduced by 50%, and the cost of global path search is reduced by 75%, and the fusion with the optimized dynamic window method can solve the local obstacle avoidance problem very well.