Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.
Keywords: Kalman filter; data fusion; exoskeleton robot; inertial measurement unit; visual measurement unit.