IEEE Trans Cybern. 2022 Dec;52(12):13237-13249. doi: 10.1109/TCYB.2021.3107357. Epub 2022 Nov 18.
Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This range of applications raises a great number of theoretical and practical challenges arising mainly from the unknown human-robot interaction model as well as from the difficulty of accurately model the robot dynamics. In this article, an adaptive impedance controller for human-robot co-transportation is put forward in task space. Vision and force sensing are employed to obtain the human hand position, and to measure the interaction force between the human and the robot. Using the latest developments in nonlinear control theory, we propose a robot end-effector controller to track the motion of the human partner under actuators' input constraints, unknown initial conditions, and unknown robot dynamics. The proposed adaptive impedance control algorithm offers a safe interaction between the human and the robot and achieves a smooth control behavior along the different phases of the co-transportation task. Simulations and experiments are conducted to illustrate the performance of the proposed techniques in a co-transportation task.
人机共乘允许人和机器人在共享环境中协同执行物体运输任务。这一系列应用带来了许多理论和实际的挑战，主要源于未知的人机交互模型以及准确建模机器人动力学的困难。本文在任务空间中提出了一种用于人机共乘的自适应阻抗控制器。视觉和力感测用于获取人手位置，并测量人与机器人之间的相互作用力。利用非线性控制理论的最新进展，我们提出了一种机器人末端执行器控制器，以在执行器输入约束、未知初始条件和未知机器人动力学的情况下，跟踪人类伙伴的运动。所提出的自适应阻抗控制算法提供了人与机器人之间的安全交互，并在共乘任务的不同阶段实现了平滑的控制行为。进行了仿真和实验，以说明在共乘任务中提出的技术的性能。
