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首页> 外文会议>Joint IEEE International Conference on Development and Learning and Epigenetic Robotics >A Novel Pneumatic Artificial Muscle -driven Robot for Multi-joint Progressive Rehabilitation
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A Novel Pneumatic Artificial Muscle -driven Robot for Multi-joint Progressive Rehabilitation

机译：一种新型气动人工肌肉，用于多关节渐进康复的机器人

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摘要

Due to the bio-mechanical characteristics and inherent compliance, pneumatic artificial muscles have been widely applied in rehabilitation robotic field. However, the most existing multi-joint rehabilitation robots have the disadvantages of bulky facilities, low utilization rate and high cost; while some rehabilitation robots with simple mechanism are only suitable for a specific joint rehabilitation. This paper presents a single degree of freedom rehabilitation robot with progressive adjustation ability, which can provide suitable assistance for different patient's injury site. By introducing the joint motion radius element, the robot's mechanical parameters, fixed position, drive unit's overhanging state can be adjusted to provide the required range of motion and assistance torque to adapt to each recovery period during the whole rehabilitation process. After the kinematics and dynamics model of the joint mechanism is established, a modified sliding mode control method based on RBF neural network is utilized to compensate the system disturbance and guarantee the robust stability of the control. The experimental results show that the adopted algorithm achieved better control performance than the traditional sliding mode control method, which is suitable for the rehabilitation training of patients during the entire progressive rehabilitation periods.
机译：由于生物力学特性和固有的顺应性，气动人工肌肉已广泛应用于康复机器人领域。然而，最现有的多关节康复机器人具有庞大的设施，利用率低和成本高的缺点;虽然一些具有简单机制的康复机器人仅适用于特定的联合康复。本文介绍了具有渐进调节能力的单一自由康复机器人，可以为不同患者的损伤部位提供合适的帮助。通过引入关节运动半径元件，可以调节机器人的机械参数，固定位置，驱动单元的悬垂状态，以提供所需的运动范围和辅助扭矩，以适应整个康复过程中的每个恢复周期。在建立联合机构的运动学和动力学模型之后，利用基于RBF神经网络的改进的滑模控制方法来补偿系统干扰并保证控制的稳定稳定性。实验结果表明，采用算法比传统的滑模控制方法实现了更好的控制性能，适用于在整个渐进康复期间对患者的康复训练。

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