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首页> 外文期刊>Journal of guidance, control, and dynamics >Decentralized Geolocation and Bias Estimation for Uninhabited Aerial Vehicles with Articulating Cameras
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Decentralized Geolocation and Bias Estimation for Uninhabited Aerial Vehicles with Articulating Cameras

机译：铰接式摄像机的无人飞行器的分散地理位置和偏差估计

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摘要

The cooperative geolocation of a point of interest using multiple uninhabited aerial vehicles with articulating camera sensors is addressed, where there are non-zero-mean errors (biases) in the estimate of the uninhabited aerial vehicle state. The proposed approach is to use the onboard navigation solution in the estimator and, further, to consider biases across all uninhabited aerial vehicles and to jointly estimate both the biases and the unknown point-of-interest location. Furthermore, a decentralized solution is presented that uses marginalization of the biases, thus allowing the uninhabited aerial vehicles to share only information about the point of interest and model only their local biases. This decentralized approach saves significant computation and scales well with the number of uninhabited aerial vehicles. Real flight-test data and hardware-in-the-loop simulations are used to demonstrate the improvement in geolocation with bias estimation, as well as the effectiveness of the new decentralized point of interest and bias estimation algorithm, for both stationary and moving points of interest.
机译：解决了使用多个具有铰接式摄像机传感器的无人飞行器对兴趣点进行协作地理定位的问题，其中无人飞行器状态的估计中存在非零均值误差（偏差）。所提出的方法是在估算器中使用机载导航解决方案，并且进一步考虑所有无人飞行器上的偏差，并共同估算偏差和未知的兴趣点位置。此外，提出了一种分散的解决方案，该方案使用偏差的边缘化，从而允许无人驾驶的飞行器仅共享有关兴趣点的信息，并仅对其局部偏差进行建模。这种分散的方法可以节省大量计算，并且可以随着无人驾驶飞机的数量而扩展。实际的飞行测试数据和半实物仿真用于通过偏差估计来证明地理位置的改进，以及新的分散兴趣点和偏差估计算法对于固定点和运动点的有效性。利益。

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