• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2024, Vol. 60 ›› Issue (17): 111-122.doi: 10.3901/JME.2024.17.111

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Design and Analysis of a Parallel Cable Driven Lower Limb Rehabilitation Robot for Multi Joints Training

ZHANG Yuze1, ZHAO Jingfu1, ZHAO Zhenwei1, KANG Rongjie1,2,3, DAI Jiansheng4,5, SONG Zhibin1,2,3   

  1. 1. School of Mechanical Engineering, Tianjin University, Tianjin 300354;
    2. Key Laboratory of Mechanism Theory and Equipment Design, Ministry of Education, Tianjin University, Tianjin 300354;
    3. International Center for Advanced Mechanisms and Robotics, Tianjin University, Tianjin 300354;
    4. Institute for Robotics, Southern University of Science and Technology, Shenzhen 518055;
    5. Centre for Robotics Research, King's College London, London WC2R 2LS, UK
  • Received:2023-08-09 Revised:2024-01-19 Published:2024-10-21

Abstract: At present, rehabilitation demand in China is huge and showing a continuous growth trend, rehabilitation robots are an important means to solve this problem. In view of the limitations of existing lower limb rehabilitation robots in terms of human-computer interaction, training methods and economy, a cable-driven parallel lower limb rehabilitation robot is proposed, which realizes a wide range of movement of the user’s lower limbs through four cables distributed in parallel. The kinematics and statics model of the robot are established, and the pulley friction in the cable-driven mechanism is modeled and identified. Aiming at the problem that the user’s position is uncertain each time, a method for auto-identification of the user’s location without the help of external devices is proposed. Based on this position recognition parameter, the robot adapts the user’s rehabilitation training parameters each time to achieve a precise rehabilitation strategy. An experimental platform is built to verify the feasibility of independent identification of user position through experiments, and the law of joint torque and force is explored, and the accuracy of passive training of lower limb rehabilitation robot is tested.

Key words: lower limb rehabilitation, cable driven, position identification, frictional force, soft rehabilitation robot

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