Robot Path Planning Optimization Based on RRT and APF Fusion Algorithm

In the current research field, aiming at the problem of robot path planning, this study proposes an optimization strategy combining RRT algorithm and APF method. This strategy aims to achieve more efficient and reliable robot path planning by improving the path search efficiency of RRT algorithm and combining the goal-oriented and obstacle-avoiding capability of APF. Specifically, we optimize the RRT algorithm as follows: First, we introduce an APF-based heuristic strategy, which helps guide the path search process closer to the target point faster; Secondly, in the process of path generation, the APF method is used to smooth the path in real time to reduce the complexity of the path and the energy consumption during execution. After extensive testing in simulation environments, the optimization strategy shows significant improvements in path length, planning time, and obstacle avoidance. Compared with the traditional RRT algorithm, the new strategy not only reduces the path length, but also shows stronger adaptive ability and robustness in the face of complex environment and sudden obstacles. In addition, through the path smoothing process guided by APF, the dynamic response and stability of the robot when executing the path are also improved.