The RRT-GA algorithm to improve computing efficiency of robot arm motion planning problem

This paper presents a novel algorithm that integrates the Rapidly-exploring Random Tree (RRT) and Genetic Algorithm (GA) for effective trajectory planning of robotic arms. The primary objective is to enhance motion planning and obstacle avoidance in robotic applications. The proposed method significantly reduces computation time compared to standalone RRT and GA algorithms, while also achieving smoother trajectories. Experimental results demonstrate the effectiveness of the integrated approach in real-world scenarios, highlighting its potential for improving robotic arm performance in various settings.