Accurate localisation of unmanned aerial vehicles is vital for the next generation of automation tasks. This paper proposes a minimum energy filter for velocity-aided pose estimation on the extended special Euclidean group. The approach taken exploits the Lie-group symmetry of the problem to combine Inertial Measurement Unit (IMU) sensor output with landmark measurements into a robust and high performance state estimate. We propose an asynchronous discrete-time implementation to fuse high bandwidth IMU with low bandwidth discrete-time landmark measurements typical of real-world scenarios. The filter's performance is demonstrated by simulation.

中文翻译：

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一种用于无人机定位的最小能量滤波器

无人机的准确定位对于下一代自动化任务至关重要。本文在扩展的特殊欧几里得群上提出了一种用于速度辅助姿态估计的最小能量滤波器。所采用的方法利用问题的李群对称性将惯性测量单元 (IMU) 传感器输出与地标测量相结合，形成稳健且高性能的状态估计。我们提出了一种异步离散时间实现，将高带宽 IMU 与现实世界场景中典型的低带宽离散时间地标测量相融合。滤波器的性能通过仿真来证明。