Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A ∗ Algorithm

Abstract

Path planning is one of the most popular researches on mobile robots, and it is the key technology to realize autonomous navigation of robots. Aiming at the problem that the mobile robot may collide or fail along the planned path in an environment with random obstacles, a robot path planning scheme that combines the improved A ${}^{\ast }$ algorithm with an enhanced dynamic window method is proposed. In the improved A ${}^{\ast }$ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. In order to achieve local obstacle avoidance and pursuit of dynamic target points in dynamic and complex environments, an online path planning method combining enhanced dynamic window algorithm and global path planning information is proposed. The preview deviation angle tracking method is used to successfully capture moving target points. It also improves the efficiency of path planning and ensures that on the basis of the global optimal path, the random obstacle can be avoided in real time so that the robot can reach the target point smoothly. The simulation results show that compared with other methods, the proposed method achieves excellent global and local path planning performance, the planned trajectory is smoother, and the search efficiency is higher in complex environments.