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Purpose The purpose of this paper is to design an exoskeleton robot and present a corresponding rehabilitation training method for patients in different rehabilitation stages. Design/methodology/approach This paper presents a lightweight seven-degrees-of-freedom (DOF) cable-driven exoskeleton robot that is wearable and adjustable. After decoupling joint movement caused by a cable-driven mechanism, active rehabilitation training mode and passive rehabilitation training mode are proposed to improve the effect of rehabilitation training. Findings Simulations and experiments have been carried out, and the results validated the feasibility of the proposed mechanism and methods by a fine rehabilitative effect with different persons. Originality/value This paper designed a 7-DOF cable-driven exoskeleton robot that is suitable for patients of different body measurements and proposed the active rehabilitation training mode and passive rehabilitation training mode based on the cable-driven exoskeleton robot.

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In order to draw pictures on a plane, it is important for a robot arm to know the pose of the end-effecter relative to the world frame which is settled on the workplace. Visual servoing is frequently used in the hand-eye configuration of robot arms. However, 3D pose is preferred for a drawing robot. It is not only required to obtain the three dimensional position of the end effecter so that the pen can touch the paper without drilling a hole, but also required to get the direction so that the pen is always perpendicular to the drawing plane.In this paper, we proposed a monocular camera vision system for a 6DOF drawing robotic arm to estimate 3D pose of the end effecter robustly. First, a coplanar asymmetric polygonal landmark, which is a rectangle with a corner cut off to remove rotation ambiguity, is introduced. Second, the corner points of the landmark are indirectly obtained by intersection of the edges obtained using RANSAC. After that, corner points are filtered by KALMAN filter to reduce detection errors. Third, the end effecter's three dimensional pose relative to the world frame is estimated through PnP algorithm and the kinematics of robotics arm.Experiments show that the 3D vision system has been successfully applied in our robotic arm to draw a circle. The stability and robustness of hand-eye is improved in real time drawing usage. Index Terms -Hand-eye vision, Pose estimation, Perspectiven-point, KALMAN filter.

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