People with hemiplegia require ongoing rehabilitation exercises to regain function in their upper limbs. However, due to the increasing number of elderly and disabled people, the number of rehabilitation professionals is insufficient. As a solution to this problem, researchers have been exploring various upper limb rehabilitation exercise robots. Unfortunately, these robots are often large and heavy, making them cumbersome to wear and use. The proposed exoskeleton rehabilitation robot consists of two robotic modules: an elbow module (1 DOF) and a wrist module (1 DOF). In order to analyze the robot"s workspace, the kinematics were calculated using the D-H parameters. To generate the trajectories, five able-bodied individuals wore the robot and performed the hand-wash motion, resulting in a total of 10 trajectory data sets. The reference trajectories were then generated by polynomial regression based on the collected data. Lastly, a passive mode control was experimented with in the rehabilitation process, and the results demonstrated the promising effectiveness of the proposed robot.

In this paper, we propose a method to generate the trajectory of a robotic shoe sole spray system by extracting target points from a 3-D model of a mold sole. Point cloud transformation based on the mold 3-D file format, Z-Axis uppermost point extraction, elimination of unnecessary points, and final target point selection are sequentially performed. The Catmull- Rom algorithm is then applied to plan spline trajectory that allows the robot end effector to spray at a constant speed by following the extracted target points. The proposed algorithm is validated on the test bed of a shoe sole spray system. Through the proposed method, the adhesive can be uniformly dispensed to the sole of the shoe in an atypical shape without the process of extracting the work point using the vision system.