State Observability through Prior Knowledge: Tracking Track Cyclers with Inertial Sensors
State Observability through Prior Knowledge: Tracking Track Cyclers with Inertial Sensors
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DOI：
10.1109/ipin.2019.8911757
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发表时间：
2019-09
期刊：
影响因子：
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通讯作者：
Tom L. Koller;U. Frese
中科院分区：
文献类型：
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作者：
Tom L. Koller;U. Frese
惯性导航系统的位置和姿态估计存在着无限大的误差。这种漂移可以通过应用先验知识来校正，而不是使用外感受传感器。分析由先验知识引起的状态可观测性激励我们跟踪场地自行车比赛中的自行车运动员。在本文中，我们表明，骑自行车的人的姿势可以估计与IMU作为唯一的传感器，通过使用的轨道的高度图和知识，骑自行车的人驱动器向前。我们提出了一个数据集，有三个60轮的试验和评估的状态估计。我们表明，先验的影响匹配的期望来自状态可观测性分析。
Inertial Navigation Systems suffer from unbounded errors on the position and orientation estimate. This drift can be corrected by applying prior knowledge, instead of using exteroceptive sensors. Analysing the state observability induced by prior knowledge motivates us to track bikers in track cycling races. In this paper, we show that the pose of the bikers can be estimated with an IMU as the only sensor by using a heightmap of the track and the knowledge that the biker drives forward. We present a dataset with three 60-round trials and evaluate the state estimate. We show that the influences of the priors match the expectation derived from state observability analysis.