A robotic learning and generalization framework for curved surface based on modified DMP

Abstract

How to reproduce and generalize the skills acquired by demonstrating is a hot topic for researchers. (1) A compliant continuous drag demonstration system based on discrete admittance model was designed to continuously and smoothly drag or demonstrate. (2) The modified DMP including the scaling factor and the force coupling term was used to improve the poor generalization ability of the classical DMP. (3) Curve drawing experiments were carried out to show the effectiveness of our proposed learning and generalization framework.