This paper presents a novel rotational serial variable stiffness actuator (SVSA) based on an Archimedean spiral relocation mechanism (ASRM), which is applied to linearly change the position of the pivot point of a lever as well as obtain a large range of motion and adjustable stiffness. Consequently, the ASRM introduced in this work contributes to a compact structure of the mechanical design without sacrificing the continuity of adjustable stiffness. In terms of the variable stiffness mechanism, two linear springs are assembled antagonistically on a spring shaft and rotate simultaneously with the output link. To improve the spring force transmission efficiency, these displacements of the springs are set to be perpendicular to the output link. A large deflection angle can therefore be achieved to obtain high passive energy storage ability. Moreover, the SVSA is also modeled to investigate the theoretical capabilities of the output stiffness and passive energy capability. Further control experiments are performed to quantitatively evaluate the physical performance of the SVSA. Our results demonstrate that the SVSA with a proportional-derivative feedback plus feedforward controller exhibits a fast response and high accuracy for both position and stiffness regulation and tracking tasks. In addition, the real output torque measurement verifies the fidelity of the SVSA for torque generation.

Upper limb exoskeletons show promise for improving functionalities required for stroke patients. Despite recent progress, most of current upper limb rehabilitation devices are still bulky, heavy, and less compliant to be applied. This article presents a cable-driven compliant upper limb rehabilitation exoskeleton robot (CURER) with a lightweight frame and comfortable human–robot interaction. A modular series elastic actuator (SEA) was designed to provide controlled torque for each active robotic joint, and Bowden cables were applied to transfer controlled torque to distal joints. A six-bar double parallelogram mechanism was designed to implement 3 active degrees of freedom (DOFs) of a shoulder. An actuated elbow with 1 DOF and a wrist with a passive DOF were also developed for CURER. The anthropomorphic shoulder, elbow, and wrist joints can minimize misalignment between human upper limbs and the robot. The length of anthropomorphic arm was adjustable for a wide range of users. It can apply up to a 33 N·m torque in shoulder flexion/extension, abduction/adduction, intra/extra rotation, and elbow flexion/extension, with a range of 7.6–8.0 Hz position bandwidth in each actuation. CURER has a large range of motion and can provide accurate torque control for stroke patients’ requirements. Besides, a comprehensive rehabilitation strategy including robot-in-charge mode and human-in-charge mode was developed for different recovery stages. Experiments carried out on CURER actuation units demonstrated good position and impedance control performance. Finally, a virtual reality training system was developed to assist the subjects to accomplish upper limb rehabilitation efficiently.

Many human manipulation skills are force relevant, such as opening a bottle cap and assembling furniture. However, it is still a difficult task to endow a robot with these skills, which largely is due to the complexity of the representation and planning of these skills. This paper presents a learning‐based approach of transferring force‐relevant skills from human demonstration to a robot. First, the force‐relevant skill is encapsulated as a statistical model where the key parameters are learned from the demonstrated data (motion, force). Second, based on the learned skill model, a task planner is devised which specifies the motion and/or the force profile for a given manipulation task. Finally, the learned skill model is further integrated with an adaptive controller that offers task‐consistent force adaptation during online executions. The effectiveness of the proposed approach is validated with two experiments, i.e., an object polishing task and a peg‐in‐hole assembly.