A Real-time Path Planning Algorithm for Mobile Robots Based on Safety Distance Matrix and Adaptive Weight Adjustment Strategy

The fusion of the A* and the dynamic windowing algorithm is commonly used for the path planning of mobile robots in dynamic environments. However, the planned path has the problems of redundancy and low security. This paper proposes a path planning algorithm based on the safety distance matrix and adaptive weight adjustment strategy to address the above problems. Firstly, the safety distance matrix and new heuristic function are added to the traditional A* algorithm to improve the safety of global path. Secondly, the weight of the evaluation sub-function in the dynamic window algorithm is adjusted through an adaptive weight adjustment strategy to solve the problem of path redundancy. Then, the above two improved algorithms are fused to make the mobile robot have dynamic obstacle avoidance capability by constructing a new global path evaluation function. Finally, simulations are performed on grid maps, and the fusion algorithm is applied to the actual mobile robot path planning based on the ROS. Simulation and experimental results show that the fusion algorithm achieves optimization of path safety and length, enabling the robot to reach the end point safely with real-time dynamic obstacle avoidance capability.