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Estimating Three-Dimensional Body Orientation Based on an Improved Complementary Filter for Human Motion Tracking

机译:基于改进的互补滤波器的人体运动跟踪三维人体姿势估计

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摘要

Rigid body orientation determined by IMU (Inertial Measurement Unit) is widely applied in robotics, navigation, rehabilitation, and human-computer interaction. In this paper, aiming at dynamically fusing quaternions computed from angular rate integration and FQA algorithm, a quaternion-based complementary filter algorithm is proposed to support a computationally efficient, wearable motion-tracking system. Firstly, a gradient descent method is used to determine a function from several sample points. Secondly, this function is used to dynamically estimate the fusion coefficient based on the deviation between measured magnetic field, gravity vectors and their references in Earth-fixed frame. Thirdly, a test machine is designed to evaluate the performance of designed filter. Experimental results validate the filter design and show its potential of real-time human motion tracking.
机译:由惯性测量单元(IMU)确定的刚体定向被广泛应用于机器人技术,导航,康复和人机交互中。本文针对动态融合角速率积分和FQA算法计算出的四元数,提出了一种基于四元数的互补滤波算法,以支持计算效率高,可穿戴的运动跟踪系统。首先,使用梯度下降法从多个采样点确定函数。其次,该函数用于根据测得的磁场,重力矢量及其在固定地球框架中的参考之间的偏差来动态估算融合系数。第三,设计了一种测试机来评估设计滤波器的性能。实验结果验证了滤波器的设计,并显示了其实时人体运动跟踪的潜力。

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