Efficient Adaptive Collision-Free Path Planning Algorithm for Indoor Mobile Robots: Optimization and Application

An adaptive path planning algorithm was proposed, which improves upon traditional A* by integrating an improved A* algorithm with the Dynamic Window Approach (DWA). This addresses the problems of slow search speed, unsmooth paths, and poor dynamic obstacle avoidance capability. Through an “8+5” neighborhood screening, a 16-neighborhood evaluation function, and a second-order then third-order Bézier curve optimization process, a Jetson Nano+ROS(Robot Operating System) is deployed to meet the requirements of efficient and safe navigation for fire inspection robots in complex environments. The results show that, compared with the original algorithm, the proposed algorithm reduces the average number of traversed nodes by 49.23%, the number of turns in the optimized path has decreased by approximately 28.82%, decreases curvature by 66.6%, and eliminates path tangency with obstacles. This also supports real-time obstacle avoidance with integration DWA, and outperforms traditional methods.