面向复杂力交互任务的操作技能传递与控制研究

The problem that has been explored for years in robotics is how to make robots have the same strong perception capabilities as humans and perform complex operations, especially with force interaction. Solving the problem can help the robot to truly transfer from “device” to “assistant”. The transfer and control of operational skills for complex force interaction tasks is one of the frontiers of the human-robot skills transfer research field. The core of this research lies in the learning of multi-modal skill data, demonstrated in the force interaction operations process by skilled operators. And through reasonable design skill models, combined with advanced control theory and robot perception capabilities, the robot can autonomously perform complex force interaction tasks, so that robots can truly assist or even replace humans in performing common complex tasks in life. This article summarizes three important issues in this field: ① Multimodal information fusion demonstration method; ② Skill learning for force interaction tasks; ③ Skill control based on robot compliance control and intelligent skill switching based on robot perception. At last, the research status in this field will be discussed and analyzed.