An impedance control method in null-space for 7-degree-of-freedom redundant manipulators is presented in this article. The null-space impedance motion of the redundant manipulator was described in the angle domain and a null-space impedance equation was established. To successfully obtain joint angular velocity, a high-gain observer is designed. The stability of the proposed control method was proved based on passive theory. The proposed null-space impedance control method not only preserved the Cartesian space impedance characteristics of the redundant manipulator but also achieved null-space impedance control. When the manipulator interacted with the outside world, the position error of the end effector asymptotically converged due to the self-motion of the manipulator. Simulations and experiments of the general impedance control method and the proposed impedance control method verified the effectiveness of the proposed method.

Collaborative robot has been widespread application prospect, such as homes, manufacturing, and health-care etc. In physical human-robot interaction, the external force appears inevitably in contact with environment or human, especially the interactive tasks such as trajectory tracking requirements and force compliance control. In this article, a method based on interaction intention estimation, which solve the problem of trajectory tracking accuracy and force compliance control in the same direction for the 7-DOF robot, is proposed. The increased virtual force depended on the manipuility performance index and inverse kinematic solution used the kinematic decoupling method based on the redundant angle avoid the singularity of redundant robot. Then, based on interactive intention estimation, a control strategy of variable impedance sliding mode theory in the presence of virtual force and contact force is proposed to achieve the trajectory tracking. We adopted hyperbolic tangent function to alleviate the chattering problem caused by switch function and validated the control system stability by Lyapunov theorem. Finally, Matlab simulations exhibit a 97.8% of high tracking accuracy amid the external force is 43% less than variable impedance parameters. It is therefore proved that the proposed method can achieve asymptotic tracking and the compliant behavior in physical human-robot interaction.

Upper extremity exoskeleton rehabilitation robots have become a significant piece of rehabilitation equipment, and planning their motion trajectories is essential in patient rehabilitation. In this paper, a multistrategy improved whale optimization algorithm (MWOA) is proposed for trajectory planning of upper extremity exoskeleton rehabilitation robots with emphasis on isokinetic rehabilitation. First, a piecewise polynomial was used to construct a rough trajectory. To make the trajectory conform to human-like movement, a whale optimization algorithm (WOA) was employed to generate a bounded jerk trajectory with the minimum running time as the objective. The search performance of the WOA under complex constraints, including the search capability of trajectory planning symmetry, was improved by the following strategies: a dual-population search, including a new communication mechanism to prevent falling into the local optimum; a mutation centroid opposition-based learning, to improve the diversity of the population; and an adaptive inertia weight, to balance exploration and exploitation. Simulation analysis showed that the MWOA generated a trajectory with a shorter run-time and better symmetry and robustness than the WOA. Finally, a pilot rehabilitation session on a healthy volunteer using an upper extremity exoskeleton rehabilitation robot was completed safely and smoothly along the trajectory planned by the MWOA. The proposed algorithm thus provides a feasible scheme for isokinetic rehabilitation trajectory planning of upper extremity exoskeleton rehabilitation robots.

For robots with flexible joints, the joint torque dynamics makes it difficult to control. An effective solution is to carry out a joint torque controller with fast enough dynamic response. This article is dedicated to design such a torque controller based on sliding mode technique. Three joint torque control approaches are proposed: (1) The proportional-derivative (PD)-type controller has some degree of robustness by properly selecting the control gains. (2) The direct sliding mode control approach which fully utilizes the physical properties of electric motors. (3) The sliding mode estimator approach was proposed to compensate the parameter uncertainties and the external disturbances of the joint torque system. These three joint torque controllers are tested and verified by the simulation studies with different reference torque trajectories and under different joint stiffness.

Due to the deformable surface and unknown biomechanical properties of human skin tissue, it brings a large impact on the contact position and force control of robotic massage. In this paper, an adaptive hybrid impedance control method is proposed. To adapt the massage robot to the environmental changes of muscle tissues in the human massage area, a human muscle tissue model was established, and a recursive least squares algorithm was optimized to identify the model parameters online. To determine the parameters of the impedance controller, a fuzzy system between the parameters of the skin tissue model and the robot contact dynamics model was developed. To keep the robot with proper end-effector orientation and stable contact force during the massage process, an adaptive force-position hybrid control strategy is proposed. On the one hand, a position controller for adaptive attitude adjustment is used to control the move position and the normal direction of the robot. On the other hand, a force controller based on impedance control is used to ensure a stable contact force during dynamic interaction with human. Furthermore, since massage is a human contact task, the adaptive impedance control strategy also improves the interaction safety performance and contact detection. The effectiveness and feasibility of the massage system using adaptive fuzzy impedance control adapted to the variation of human muscle tissue is verified through experiments on the robot massage movement.

The inherent highly nonlinear coupling and system uncertainties make the controller design for a flexible-joint robot extremely difficult. The goal of the control of any robotic system is to achieve high bandwidth, high accuracy of trajectory tracking, and high robustness, whereby the high bandwidth for flexible-joint robot is the most challenging issue. This paper is dedicated to design such a link position controller with high bandwidth based on sliding-mode technique. Then, two control approaches ((1) extended-regular-form approach and (2) the cascaded control structure based on the sliding-mode estimator approach) are presented for the link position tracking control of flexible-joint robot, considering the dynamics of AC-motors in robot joints, and compared with the singular perturbation approach. These two-link position controllers are tested and verified by the simulation studies with different reference trajectories and under different joint stiffness.