Zi Bin, Yin Guangcai, Zhang Dan
School of Mechanical Engineering, Hefei University of Technology, Hefei 230009, China.
Lassonde School of Engineering, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada.
Sensors (Basel). 2016 Dec 14;16(12):2121. doi: 10.3390/s16122121.
In this paper a waist rehabilitation robot driven by cables and pneumatic artificial muscles (PAMs) has been conceptualized and designed. In the process of mechanism design, the human body structure, the waist movement characteristics, and the actuators' driving characteristics are the main considerable factors to make the hybrid-driven waist rehabilitation robot (HWRR) cost-effective, safe, flexible, and well-adapted. A variety of sensors are chosen to measure the position and orientation of the recovery patient to ensure patient safety at the same time as the structure design. According to the structure specialty and function, the HWRR is divided into two independent parallel robots: the waist twist device and the lower limb traction device. Then these two devices are analyzed and evaluated, respectively. Considering the characters of the human body in the HWRR, the inverse kinematics and statics are studied when the waist and the lower limb are considered as a spring and link, respectively. Based on the inverse kinematics and statics, the effect of the contraction parameter of the PAM is considered in the optimization of the waist twist device, and the lower limb traction device is optimized using particle swarm optimization (PSO) to minimize the global conditioning number over the feasible workspace. As a result of the optimization, an optimal rehabilitation robot design is obtained and the condition number of the Jacobian matrix over the feasible workspace is also calculated.
本文对一种由缆绳和气动人工肌肉(PAM)驱动的腰部康复机器人进行了概念设计。在机构设计过程中,人体结构、腰部运动特性和执行器的驱动特性是使混合驱动腰部康复机器人(HWRR)具有成本效益、安全、灵活且适应性良好的主要考虑因素。在进行结构设计的同时,选择了多种传感器来测量康复患者的位置和方位,以确保患者安全。根据结构特点和功能,HWRR被分为两个独立的并联机器人:腰部扭转装置和下肢牵引装置。然后分别对这两个装置进行了分析和评估。考虑到HWRR中人体的特征,分别将腰部和下肢视为弹簧和连杆时,研究了其逆运动学和静力学。基于逆运动学和静力学,在腰部扭转装置的优化中考虑了PAM收缩参数的影响,并采用粒子群优化(PSO)对下肢牵引装置进行优化,以在可行工作空间内最小化全局条件数。通过优化,得到了最优的康复机器人设计,并计算了可行工作空间内雅可比矩阵的条件数。