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Pose Estimation of Unmanned Aerial Vehicles Based on a Vision-Aided Multi-Sensor Fusion

机译:基于视觉辅助的多传感器融合的无人机姿态估计

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摘要

GNSS/IMU navigation systems offer low-cost and robust solution to navigate UAVs. Since redundant measurements greatly improve the reliability of navigation systems, extensive researches have been made to enhance the efficiency and robustness of GNSS/IMU by additional sensors. This paper presents a method for integrating reference data, images taken from UAVs, barometric height data and GNSS/IMU data to estimate accurate and reliable pose parameters of UAVs. We provide improved pose estimations by integrating multi-sensor observations in an EKF algorithm with IMU motion model. The implemented methodology has demonstrated to be very efficient and reliable for automatic pose estimation. The calculated position and attitude of the UAV especially when we removed the GNSS from the working cycle clearly indicate the ability of the purposed methodology.
机译:GNSS / IMU导航系统为导航无人机提供了低成本且强大的解决方案。由于冗余测量极大地提高了导航系统的可靠性,因此进行了广泛的研究以通过附加传感器来提高GNSS / IMU的效率和鲁棒性。本文提出了一种用于集成参考数据,从无人机获取的图像,大气高度数据和GNSS / IMU数据的方法,以估计无人机的准确和可靠的姿态参数。我们通过将EKF算法中的多传感器观测与IMU运动模型集成来提供改进的姿态估计。已证明,所实施的方法对于自动姿态估计非常有效且可靠。无人机的计算位置和姿态,特别是当我们从工作周期中删除GNSS时,清楚地表明了所采用方法的能力。

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