Estimation of IMU and MARG orientation using a gradient descent algorithm.

Estimation of IMU and MARG orientation using a gradient descent algorithm.
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DOI:
10.1109/icorr.2011.5975346
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发表时间:
2011-01-01
期刊:
IEEE ... International Conference on Rehabilitation Robotics : [proceedings]
影响因子:
--
通讯作者:
Vaidyanathan, Andrew
Vaidyanathan, Andrew
中科院分区:
其他
文献类型:
--
作者:
Madgwick, Sebastian O H;Harrison, Andrew J L;Vaidyanathan, Andrew

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本文提出了一种新的方向算法,旨在支持一个计算效率高,可穿戴惯性人体运动跟踪系统的康复应用。它适用于由三轴陀螺仪和加速度计组成的惯性测量单元(伊穆斯),以及也包括三轴磁力计的磁角速率和重力(MARG)传感器阵列。MARG的实现包括磁失真补偿。该算法使用四元数表示,允许加速度计和磁力计数据用于分析导出和优化的梯度下降算法,以计算陀螺仪测量误差的方向作为四元数导数。已经使用市售的取向传感器和使用光学测量系统获得的取向的参考测量来经验性地评估性能。性能也基准对适当的卡尔曼算法的方向传感器。结果表明,该算法的精度与卡尔曼算法相当,静态均方根误差< 0.8 μ m,动态均方根误差< 1.7 μ m。低计算负载和以小采样率操作的能力的含义显著降低了可穿戴惯性运动跟踪所需的硬件和功率,使得能够创建能够长时间运行的轻质、廉价的系统。
This paper presents a novel orientation algorithm designed to support a computationally efficient, wearable inertial human motion tracking system for rehabilitation applications. It is applicable to inertial measurement units (IMUs) consisting of tri-axis gyroscopes and accelerometers, and magnetic angular rate and gravity (MARG) sensor arrays that also include tri-axis magnetometers. The MARG implementation incorporates magnetic distortion compensation. The algorithm uses a quaternion representation, allowing accelerometer and magnetometer data to be used in an analytically derived and optimised gradient descent algorithm to compute the direction of the gyroscope measurement error as a quaternion derivative. Performance has been evaluated empirically using a commercially available orientation sensor and reference measurements of orientation obtained using an optical measurement system. Performance was also benchmarked against the propriety Kalman-based algorithm of orientation sensor. Results indicate the algorithm achieves levels of accuracy matching that of the Kalman based algorithm; < 0.8째 static RMS error, < 1.7째 dynamic RMS error. The implications of the low computational load and ability to operate at small sampling rates significantly reduces the hardware and power necessary for wearable inertial movement tracking, enabling the creation of lightweight, inexpensive systems capable of functioning for extended periods of time.