Toward safe and high-performance human–robot collaboration via implementation of redundancy and understanding the effects of admittance term parameters

Abstract

Summary Today, demandsin industrial manufacturing mandate humans to work with large-scale industrial robots, and this collaboration may result in dangerous conditions for humans. To deal with this situation, this work proposes a novel approach for redundant large-scale industrial robots. In the proposed approach, an admittance controller is designed to regulate the interaction between the end effector of the robot and the human. Additionally, an obstacle avoidance algorithm is implemented in the null space of the robot to prevent any possible unexpected collision between the human and the links of the robot. After safety performance of this approach is verified via simulations and experimental studies, the effect of the parameters of the admittance controller on the performance of collaboration in terms of both accuracy and total human effort is investigated. This investigation is carried out via 8 experiments by the participation of 10 test subjects in which the effect of different admittance controller parameters such as mass and damper are compared. As a result of this investigation, tuning insights for such parameters are revealed.

Special issue on recent advances in field and service robotics: handling harsh environments and cooperation

“…For the sake of enhancing work capacity and task efficiency in industry, research attention has been paid to the interactions, either among machines or between machines and humans. Addressing this problem for robotic collaboration with manipulators, Kanik, Ayit et al propose an admittance control scheme for human-robot interface via a shoulder haptic device [3]. The dynamics ratio of the end-effector's velocity and the interaction force change is controlled to follow a desired admittance function while avoiding the obstacles and driving the trajectory tracking error to zero with a PI controller.…”

Based on human-like variable admittance control for human–robot collaborative motion

“…The human–robot collaboration can combine human–environmental cognition and problem-solving abilities with robots’ advantages of high efficiency, lasting energy, and accuracy. However, how to improve the performance of human–robot collaboration (to achieve safe, compliant, and efficient human–robot collaboration) will be a challenge [5, 6].…”