In this paper, we have proposed an algorithm to combine multiple cheap Inertial Measurement Unit (IMU) sensors to calculate 3D-orientations accurately. Our approach takes into account the inherent and non-negligible systematic error in the gyroscope model and provides a solution based on the error observed during previous instants of time. Our algorithm, the {\em Best Axis Composition} (BAC), chooses dynamically the most fitted axes among IMUs to improve the estimation performance. We have compared our approach with a probabilistic Multiple IMU (MIMU) approach, and we have validated our algorithm in our collected dataset. As a result, it only takes as few as 2 IMUs to significantly improve accuracy, while other MIMU approaches need a higher number of sensors to achieve the same results.
翻译：在本文中,我们提出了一种算法,将多种廉价的惰性测量单位传感器(IMU)传感器结合起来,准确计算三维方向。我们的方法考虑到了陀螺仪模型中固有的和不可忽略的系统错误,并根据先前时段所观察到的错误提供了解决办法。我们的算法,即“最轴组成”(BAC),以动态方式选择IMU中最合适的轴来改进估计性能。我们比较了我们的方法和多维度的多MU(MIMU)方法,并在我们收集的数据集中验证了我们的算法。因此,只需要2个IMU就能显著提高准确性,而其他MIMU则需要更多传感器才能取得同样的结果。
相关内容
微信扫码咨询专知VIP会员