Zi-Qi Yang

In recent years, the focus on developing robot manipulators has shifted towards prioritizing safety in Human-Robot Interaction (HRI). Impedance control is a typical approach for interaction control in collaboration tasks. However, such a control approach has two main limitations: 1) the end-effector (EE)’s limited compliance to adapt to unknown physical interactions, and 2) inability of the robot body to compliantly adapt to unknown physical interactions. In this work, we present an approach to address these drawbacks. We introduce a modified Cartesian impedance control method combined with a Dynamical System (DS)-based motion generator, aimed at enhancing the interaction capability of the EE without compromising main task tracking performance. This approach enables human coworkers to interact with the EE on-the-fly, e.g. tool changeover, after which the robot compliantly resumes its task. Additionally, combining with a new null space impedance control method enables the robot body to exhibit compliant behaviour in response to interactions, avoiding serious injuries from accidental contact while mitigating the impact on main task tracking performance. Finally, we prove the passivity of the system and validate the proposed approach through comprehensive comparative experiments on a 7 Degree-of-Freedom (DOF) KUKA LWR IV+ robot.

In recent years, the focus on developing robot manipulators has shifted towards prioritizing safety in Human-Robot Interaction (HRI). Impedance control is a typical approach for interaction control in collaboration tasks. However, such a control approach has two main limitations: 1) the end-effector (EE)'s limited compliance to adapt to unknown physical interactions, and 2) inability of the robot body to compliantly adapt to unknown physical interactions. In this work, we present an approach to address these drawbacks. We introduce a modified Cartesian impedance control method combined with a Dynamical System (DS)-based motion generator, aimed at enhancing the interaction capability of the EE without compromising main task tracking performance. This approach enables human coworkers to interact with the EE on-the-fly, e.g. tool changeover, after which the robot compliantly resumes its task. Additionally, combining with a new null space impedance control method enables the robot body to exhibit compliant behaviour in response to interactions, avoiding serious injuries from accidental contact while mitigating the impact on main task tracking performance. Finally, we prove the passivity of the system and validate the proposed approach through comprehensive comparative experiments on a 7 Degree-of-Freedom (DOF) KUKA LWR IV+ robot.

This paper studies the working principles of antagonistic magneto-rheological (MR) actuators, i.e., a combination of an electric motor and a pair of MR clutches in an antagonistic configuration, for compliant actuation in robotics. The study focuses on the unique boundedness property exhibited by MR actuators, which limits the output torques delivered to the load, independent of the received input torque and/or control commands. This inherent property is of significant importance for ensuring human safety in human–robot interaction applications. Through a comprehensive analysis, we provide analytical proof of the inherent output boundedness of antagonistic MR actuators and validate our findings through experimental results. Our research demonstrates that these actuators are well-suited for safe operations in robotic applications, eliminating the need for additional sensor measurements or complex control strategies. This promising capability enables the avoidance of trade-offs between actuator performance, complexity, and cost. The insights gained from this study contribute to advancing compliant actuation technology, paving the way for high-performance and human-safe robotic systems.

The collaborative robot market has experienced rapid growth, leading to advancements in compliant actuation and torque control. Magneto-rheological (MR) clutches offer a hardware-level solution for achieving both compliance and torque control through adjustable coupling between the input and output of the MR clutch. However, the presence of frequency-dependent magnetic hysteresis makes controlling the output torque challenging. In this paper, we present a comparative study of six widely used hysteresis models and propose a computationally efficient algebraic model to address the issue of hysteresis modeling and control of the output torque of rotary MR clutches. We compare the estimated torques with experimental measurements from a prototype MR clutch, to evaluate the computational complexity and accuracy of the model. Our proposed algebraic hysteresis model demonstrates superior accuracy and approximately two times less computational complexity than the Bouc–Wen model, and approximately twenty times less memory requirement than neural network-based models. We show that our proposed model has excellent potential for embedded indirect torque control schemes in systems with hysteresis, such as MR clutches and isolators.