一种新型气动人工肌肉驱动多关节渐进式康复机器人

Xingxing Guo, Quan Liu, Jie Zuo, W. Meng, Qingsong Ai, Zude Zhou, Wenjun Xu
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引用次数: 1

摘要

气动人工肌肉由于其生物力学特性和固有的顺应性,在康复机器人领域得到了广泛的应用。然而,现有的多关节康复机器人大多存在设备体积大、利用率低、成本高等缺点;而一些机构简单的康复机器人只适用于特定的关节康复。本文提出了一种具有进行性调节能力的单自由度康复机器人,可以针对不同的患者损伤部位提供合适的辅助。通过引入关节运动半径元素,可以调整机器人的机械参数、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各个恢复阶段。在建立关节机构的运动学和动力学模型后,采用基于RBF神经网络的改进滑模控制方法补偿系统扰动,保证控制的鲁棒稳定性。实验结果表明,所采用的算法比传统的滑模控制方法取得了更好的控制性能,适用于患者在整个渐进式康复期间的康复训练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Novel Pneumatic Artificial Muscle -driven Robot for Multi-joint Progressive Rehabilitation
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.
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