An improved A algorithm for the industrial robot path planning with high success rate and short length

• Published in: Robotics and autonomous systems Vol. 106; pp. 26 - 37
• Main Authors: Fu, Bing, Chen, Lin, Zhou, Yuntao, Zheng, Dong, Wei, Zhiqi, Dai, Jun, Pan, Haihong
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.08.2018
• Subjects: Improved A algorithm; Path optimization; Path planning; Robot manipulator; Path optimization; Path planning; Improved A algorithm; Robot manipulator
• ISSN: 0921-8890; 1872-793X
• DOI: 10.1016/j.robot.2018.04.007

Intelligent path planning is a significant tool for field of industrial robot. This field has attracted the attention of numerous researchers due to the great market demands, broad application prospects, and large potential development. Due to the limitation of neighborhood, the path search by the original A* algorithm is more likely to fail, and the solved path may contain too many local paths. In this study, an improved A* algorithm is proposed to solve the robot path planning problem. The first improvement of the advanced method is the local path between the current node and the goal node, which is planned before the next search in the neighborhood of the current node. And the local path will be adopted directly if it is safe and collisionless. The second advantage of this method is the utilization of post-processing stage to optimize the resulting path, by straightening the local path to reduce the number of local paths as well as the path length. In order to verify the theoretical advantages of the improved A* algorithm, a series of two-dimensional figures of the robot task was presented in this paper. In addition, some comparative experiments in the virtual and real robot manipulator platform are performed to examine the improved A* algorithm. Experimental results show that the search success rate of the improved A* algorithm is higher than the original A* algorithm, along with a shorter and smoother path could be obtained by the improved A* algorithm. Therefore, the success rate of robot path planning and the optimal extent of the robot path are effectively improved by the improved A* algorithm. •Focus on path planning for industrial robots in complex environments.•A local safety and collisionless path was built between the sampling points by local path planner.•The local path to the goal node is planned before the next search in the neighborhood of the current node.•A post-processing stage used to optimize the resulting path.•Path planning problem is solved by the improved A* algorithm with high search success rate and short length.