The wearable powered exoskeleton is a human-robot cooperation system that integrates the strength of a robot with human intelligence. This paper presents the research results into a powered hip exoskeleton (PH-EXOS) designed to provide locomotive assistance to individuals with walking impediments. The Bowden cable actuated exoskeleton has an anthropomorphic structure with six degrees of freedom (DOF) in order to match the human hip anatomy and enable natural interaction with the user. The mechanical structure, the actuation system, and the interaction kinematics of PH-EXOS are optimized to achieve preferable manoeuvrability and harmony. For the control of the exoskeleton, a real-time control system is established in xPC target environment based on Matlab/ RTW. A Cascaded PID controller is developed to perform the trajectories tracking tasks in passive control mode. Besides, based on the pressure information on the thigh, a fuzzy adaptive controller is developed to perform walking assistance tasks in active control mode. Preliminary treadmill walking experiments on a healthy subject were conducted to verify the effectiveness of the proposed device and control approaches in reducing walking effort.

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Robot-assisted therapy has become an important technology applied in rehabilitation engineering, allowing patients with motion impairment problems to perform training programs without continuous supervision from physiotherapists. The goal of this paper is to develop a gravity balanced exoskeleton for active rehabilitation training of upper limb. The mechanical structure and kinematics of the exoskeleton are described and optimized to enable natural interaction with user and avoid singular configurations within the desired workspace. The gravity balancing of the human arm and mechanism is achieved through a hybrid strategy making use of auxiliary links and zero-free-length springs to balance the effect of gravity over the range of motion. The balance errors resulting from the variation of anthropometric parameters are analyzed and discussed. Further experiments involving trajectories tracking tasks with and without gravity balancing are conducted to evaluate the improvement of the control performance and energetic efficiency made by the developed balanced mechanism. The experimental results indicate that the proposed balance strategy can achieve a reduction of 34.56% in overall power consumption compared with the cost in unbalanced condition.

Robot-assisted therapy has played a significant role in helping the disabled patients to restore motor functions. In this paper, a redundant exoskeleton is developed for upper-limb rehabilitation. An analytical methodology for obtaining the inverse kinematic solution of the exoskeleton is presented to provide synchronized movement with patients and ensure natural human–robot interaction. To mathematically express the redundancy problem, the swivel angle of elbow is introduced as an additional parameter to specify the human arm congratulation with a predefined wrist location. A kinematic criterion is proposed to determine the swivel angle by imitating the natural reflexive reaction of human arm. The effectiveness of the proposed strategy is experimentally evaluated via four representative types of upper-limb motion tasks. During the experiments, the actual kinematic data of human arm is collected by utilizing an articulated motion capture system integrated with inertial sensors and, after that, compared to the estimation results generated by the proposed redundancy resolution. The experimental results indicate that the kinematic criterion of swivel angle is suitable to describe the free reaching movement without additional constraints. Moreover, with the estimated swivel angles, the root mean square errors between the actual and calculated joint angles are normally less than 8[Formula: see text].

The applications of robotics and automation technology to the therapies of neuromuscular and orthopedic impairments have received increasing attention due to their promising prospects. In this paper, we present an actuated upper extremity exoskeleton aimed to facilitate the rehabilitation training of the disable patients. A modified sliding mode control strategy incorporating a proportional-integral-derivative sliding surface and a fuzzy hitting control law is developed to ensure robust and optimal position control performance. Dynamic modeling of the exoskeleton as well as the human arm is presented and then applied to the development of the fuzzy sliding mode control algorithm. A theoretical proof of the stability and convergence of the closed-loop system is presented using the Lyapunov theorem. Three typical real-time position control experiments are conducted with the aim of evaluating the effectiveness of the proposed control scheme. The performances of the fuzzy sliding mode control algorithm are compared to those of conventional proportional-integral-derivative controller and conventional sliding mode control algorithm. The experimental results indicate that the position control with fuzzy sliding mode control algorithm has a bandwidth about 4 Hz during operation. Furthermore, this control approach can guarantee the best control performances in term of tracking accuracy, response speed, and robustness against external disturbances.