Human demonstration data for fast task teaching

Abstract

Robot operation requires a succinct interface with fewer parameters to specify. This paper presents an algorithm to interface an integrated torque control law, and human task demonstration data. The data is comprised of 6 degrees of freedom, pendant force and position data, and hand posture tracking data. The aim is to automatically specify all the required parameters for the control law, which include constrained and non-constrained trajectories, reference task frames and distal end compliance. The algorithm is embedded with functions to optimise, filter, synchronise and enhance safety.