Robotic Arms Passing Through Obstacle Nodes: Using an Improved Intelligent Algorithm

Abstract

In the working process, how efficiently the robotic arm passes the obstacle nodes has a great impact on its working efficiency. This paper briefly introduced the rapidly exploring random tree (RRT) algorithm and optimized it with the gravitational potential function based on its shortcomings. The B-spline curve was used to smooth the path. Experimental analyses were carried out in two-dimensional and three-dimensional environments. It was found that the improved RRT algorithm had an average running time of 0.39 s and an average path length of 93.96 mm in the two-dimensional environment; taking environment 1 as an example, the average running time and path length of the improved RRT algorithm was 1.03 s and 147.63 mm, respectively, in the threedimensional environment, after passing through seven path nodes, which were significantly better than the standard RRT algorithm. The results prove the effectiveness of the improved intelligent algorithm for robotic arm path optimization selection. The improved RRT algorithm can be further promoted and applied in practice.