Force tracking control for motion synchronization in human-robot collaboration

Abstract

In this paper, motion synchronization is investigated for human-robot collaboration such that the robot is able to "actively" follow its human partner. Force tracking is achieved with the proposed method under the impedance control framework, subject to uncertain human limb dynamics. Adaptive control is developed to deal with point-to-point movement, and learning control and neural networks (NN) control are developed to generate periodic and arbitrary continuous trajectories, respectively. Stability and tracking performance of the closed-loop system are discussed through rigorous analysis. The validity of the proposed method is verified through simulation and experiment studies.

Reference Adaptation for Robots in Physical Interactions With Unknown Environments

“…According to (31), if lim t→∞ Z(t) = 0 and lim t→∞Ż (t) exists, then lim t→∞ ε(t) = 0, since Λ is positive definite. Therefore, the control objective of the adaptive impedance control is to make…”

“…In [29], human's moving direction is estimated using the Kalman filter and it is used for the position control of the robot. In [30], [31], human's motion intention is estimated by minimizing the interaction force and the robot's reference trajectory is adapted accordingly. The above research works [25], [26], [27], [28], [29], [30], [31] mainly focus on reference adaptation based on human's motion intention, and the control objective is to minimize the interaction force between human and robot and the desired reference trajectory is considered to be the same as human's intention.…”

Improving human-robot interactivity for tele-operated industrial and service robot applications

“…Secondly, in this application we introduce the concept of shared control [9], [10], [11]. Because of the low situation awareness in a remotely operated robot task, if the operator is given full access of the robot's 6-DoF workspace, he has to devote much of his effort to control the extra DoFs that ensure the successful completion of the task rather than the task action itself.…”

Advanced Mathematical Methods for Collaborative Robotics

“…Robot Guidance. The forces/torques exerted by the operator are usually obtained with a force sensor mounted at the robot wrist and the measurements of the sensor are typically converted into robot motions using compliance control [4]; however, other variants and methods can be found in the literature; see [5,6] among others.…”