Enhanced path planning for industrial robot: integrating modified artificial potential field and A* algorithm / Fan Rui ... [et al.]

The study proposes a modified Artificial Potential Field (APF) method integrated with the A* algorithm to enhance industrial robot path planning for obstacle avoidance. This approach addresses issues of local minima and unreachable targets within APF, mitigates the A* algorithm's poor real-time performance, and enhances obstacle avoidance success rates. Kinematic and workspace analyses of the robot utilize the Denavit-Hartenberg and Monte Carlo methods. The study analyses the principles and limitations of classical algorithms. The study introduces a modified APF algorithm to address issues of local minima and path oscillation, which is integrated with A* to guide movement towards the virtual target. After getting rid of local minima, the algorithm reverts to the APF method for further searching. Introducing a safe distance to restrict the repulsive field's influence resolves the issue of unreachable targets. Simulation results demonstrate that the modified algorithm efficiently plans obstacle-free paths in multi-obstacle environments, with target error controlled within 0.0121 m.