Skill robot library: Intelligent path planning framework for object manipulation

Abstract

Commonly used path planning techniques for object manipulation are computationally expensive and time-consuming. In this paper, a novel framework called Skill Robot Library (SRL), which has competence to store only the keypoints of a path rather than complete, is presented. The path can be computed with path planner or taught by a human using kinesthetic teaching. Additionally, when the environment is static and only the requested new start and goal positions are changed with respect to the start and goal positions of the stored path, the SRL can retrieve and modify the stored path. The SRL forwards the final path to the robot for reproduction. Experimental results achieved with a six degrees of freedom robotic arm are presented together with performance evaluation of the SRL and the path planner is demonstrated via a series of experiments.