A Dynamic Multiple-Query RRT Planning Algorithm for Manipulator Obstacle Avoidance

Manipulator motion planning for real-time obstacle avoidance in a dynamic environment is explored this article. To address problems, multiple-query and sampling-based replanning algorithm with the bias-goal factor, rapidly exploring random tree (DBG-RRT), proposed to achieve rapid response high success rate. Differently from other studies on path planning, relay-node method adopted basis of generate new collision-free trajectory. Subsequently, an un-interrupt strategy embraced judge whether generated trajectory would be interfered by obstacles. In end, DBG-RRT applied, results demonstrate its effectiveness manipulator environment.