Enhanced Path Planning for Industrial Robot: Integrating Modified Artificial Potential Field and A* Algorithm

• 發表在: Journal of Mechanical Engineering
• 主要作者: Rui F.; Ayub M.A.; Patar M.N.A.A.; Abdullah S.C.; Ruslan F.A.
• 格式: Article
• 語言: English
• 出版: UiTM Press 2024
• 在線閱讀: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215691232&doi=10.24191%2fjmeche.v13i1.3761&partnerID=40&md5=4430c68a6050a51b12dfcdbc3212131c

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. © (2024), (UiTM Press). All rights reserved.