Predictive Assistive Motion Generation Based on Human Intent for Human-Collaborative Robots

Abstract

In this paper, a method is proposed to estimate the velocity of the hand cooperating with the robot as human intent based on human surface electromyography signals, and to make the robot move in a predictive assistive motion. Specifically, an index to measure the matching index between human hand velocity and robot motion is proposed, based on the estimation of human hand velocity from human surface electromyography signals by a recurrent neural network, and using this as the human intent. Furthermore, the strength of the robot's support is adjusted based on the matching index to achieve predictive assistive motion behavior of the robot during cooperative work. In the experiment, an index to measure the burden of human work was defined, and the effectiveness of the proposed method was verified. Specifically, the proposed method was implemented and evaluated for the task of manipulating an object in cooperation with an impedance-controlled robot. The results show that the proposed method can reduce the burden on humans.