Human–Robot Interaction Control Based on a General Energy Shaping Method

Abstract

Coexistence of the human and robot in the same workspace requires the robot to perform robot tasks, such as trajectory tracking, and also interaction tasks, such as keeping a safe distance with the human. According to various human–robot interaction (HRI) scenarios, different interaction tasks usually require different task requirements or specifications, leading to different control strategies. Besides, due to different natures of the robot tasks and interaction tasks, different controllers may be required when the task is switched from one to another. So far, there is no theoretical framework that integrates different robot and interaction task requirements into a unified robot control strategy. In this article, a general HRI control framework is proposed for the scenario of the human and robot coexisting in the same workspace. We propose a general potential energy function that can be used to derive a stable and unified controller for various robot tasks and HRI tasks. By using the proposed method, various tasks can be specified at a user level by simply adjusting certain task parameters. Interactive weights are also defined to specify the interaction behaviors of robots according to different HRI applications. A human-dominant interaction mode is presented to demonstrate the applications of the proposed method. We show how the control framework can be applied to existing robot control systems with the velocity control or torque control mode by developing a joint velocity reference command and an adaptive controller. The stability of the adaptive control system is shown by using Lyapunov-like analysis. The control methods are implemented on two industrial manipulators and experimental results are presented to illustrate the effectiveness of the proposed control framework.