The sensing system of body movement is the key to realize compliant control and human-robot coupling for the exoskeleton robot. The dynamic model of the lower limb was analyzed and the cooperative control method was brought forward. Position control method was applied in the support phase, and the interactive-force based admittance control method was applied in the swing phase. According to the method, the sensing system of lower limb exoskeleton robot based on multi-information fusion was developed, which employed joints angle of body, human-machine interaction force and plantar pressure as perceptual parameters. Using the variable-gain Kalman fliter algorithm to process the angle measured by IMU sensor and the Savitzky-Golay filter algorithm to process the pressure measured by FSR, the gait characteristic was acquired and the test was carried out to verify the reliability of the method. The experimental results showed that the attitude angle calculating algorithm of IMU data had the characteristics of high precision and good stability, and the human-robot interactive method and the FSR pressure data processing algorithm were feasible, which meant that the sensing system had the reliable ability to acquire and fuse attitude angle, interaction force and plantar pressure and identify the wearer's gait accurately. The results can provide a reference for optimizing the sensing system of exoskeleton robot and promote the development of the control systems and strategies of exoskeleton robot.
HUANG Zi-liang,Fang Chen-hao,OUYANG Xiao-ping et al. Research on the sensing system of lower limb exoskeleton robot based on multi-information fusion[J]. Chinese Journal of Engineering Design, 2018, 25(2): 159-166.