Design and control of a 4-DOF cable-driven arm rehabilitation robot (CARR-4)

• Published in: 2017 IEEE International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM) pp. 581 - 586
• Main Authors: Zhongyi Li, Weihai Chen, Jianbin Zhang, Shaoping Bai
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.11.2017
• Subjects: Conferences; Random access memory
• ISSN: 2326-8239
• DOI: 10.1109/ICCIS.2017.8274842

Robotic rehabilitation devices for patients with motor dysfunction can provide effective rehabilitation training. In this paper, a 4 degree-of-freedom cable-driven arm rehabilitation robot (CARR-4) and its controller have been proposed for shoulder and elbow rehabilitation training. The exoskeleton of CARR-4 consists of a 3-DOF shoulder module and a 1-DOF elbow module, and each of them can be controlled independently. Moreover, a mechanical design for a comfortable human-robot physical interface is considered. The controller is primarily based on a robust adaptive iterative learning control (ILC) algorithm, which aids in compensating the model uncertainties and external disturbance, improving the tracking performance. Through simulations, the proposed controller is evaluated to satisfy the function requirement. Preliminary experiments are conducted on the prototype of CARR-4 for a repetitive task, which show the tracking errors are successfully improved.