Mobile Robot Path Planning Algorithm Based on A* Algorithm and Dynamic Window Approach for Autonomous Navigation

This paper presents hybrid path-planning algorithms designed to address the challenge of guiding mobile robot through an environment with global path-planning-based A* graph-search algorithm to obtain the optimal path from the start to the goal location for static and known environment; on the other hand, local path-planning uses the Dynamic Window Approach (DWA) to avoid obstacles and follow a global path generated, to obtain a smooth trajectory for the mobile robot. Simulation results demonstrate the effectiveness of a hybrid path-planning algorithm for verifying obstacle avoidance and goal-seeking behaviours, thereby increasing navigation efficiency in complex environments. The hybrid algorithm optimally combines multiple techniques to ensure reliable and efficient movement, with performance evaluated through metrics such as path length, computation time, and success rate.