An Observation Based Method for Human Robot Writing Skill Transfer
Xian Li, Weiyong Si, Chenguang Yang · 2022
This paper proposes a novel method of Chinese character stroke extraction and a framework for human robot skill transfer through vision-based observation. By analyzing the structure of Chinese characters, a direction vector update rule and a pixel finding rule were proposed to find the basic strokes. Then we designed a basic stroke connection algorithm to achieve stroke extraction. Afterward, to adapt to human interference in real-time, we adopt dynamical movement primitives (DMPs) to model writing skills. Finally, the adaptive capability of the method was verified by experiments in which the robot writes Chinese characters on a randomly moved writing board.