Intelligent Robotic Peg-in-Hole Insertion Learning Based on Haptic Virtual Environment

Abstract

A new approach is explored to transfer human manipulation skills to a robotics system. A skill acquisition algorithm utilizes the position and contact force/torque data generated in the virtual environment combined with a priori knowledge about the task to generate the skills required to perform such a task. Such skills are translated into actual robotic trajectories for implementation in real time. The peg-in-hole insertion problem is used as a case study. The results are reported.