Motion Planning by T-RRT with Potential Function for Vertical Articulated Robots

Abstract

RRT (rapidly-exploring random tree) with random sampling is an effective method for path planning, and is often used for robot manipulators. The RRT has many modified methods for applying various problems and conditions. Particularly, T-RRT (Transition-based RRT) one of those has advantage that it is able to adopt arbitrary evaluation function. In this paper, a novel path planning method based on the T-RRT is proposed for ensuring ”quality” of a generated path. Then, its effectiveness is evaluated via comparison with other sampling-based methods using simulation of the industrial robot having seven degrees of freedom.