A Novel Biomechanical Model-Aided IMU/UWB Fusion for Magnetometer-Free Lower Body Motion Capture
提出一种无磁力计的下半身运动捕捉算法，融合惯性传感器、超宽带定位和生物力学模型，消除偏航角漂移，在磁干扰环境下优于传统方法，定位精度优于4.5厘米，膝关节角度跟踪精度约3.5°至4.5°。
The available human body inertial motion capture (MoCap) systems are aided by magnetometers to remove the drift error in yaw angle estimation, which in turn limits their application in the presence of long-lasting magnetic disturbances in indoor environments. This paper introduces a magnetometer-free algorithm for lower-body MoCap including 3-D localization and posture tracking by fusing inertial sensors with an ultrawideband (UWB) localization system and a biomechanical model of the human lower body. Using our novel Kalman filter-based fusion algorithm, the UWB localization data aided by the biomechanical model can eliminate the drift in inertial yaw angle estimation of the lower-body segments. This magnetometer-free yaw angle estimation makes the algorithm insensitive to the magnetic disturbances. The algorithm is benchmarked against the optical MoCap system for various indoor activities including walking, jogging, jumping, and stairs ascending/descending. The results show that the proposed algorithm outperforms the available magnetometer-aided algorithms in yaw angle tracking under magnetic disturbances. In a uniform magnetic field, the algorithm shows similar accuracies in localization and joint angle tracking when compared with the magnetometer-aided methods. The localization accuracy of the proposed method is better than 4.5 cm in a 3-D space and its accuracy for knee angle tracking is about 3.5° and 4.5° in low and high dynamic motions, respectively.