论文标题
无人驾驶飞机定位的最低能量过滤器
A Minimum Energy Filter for Localisation of an Unmanned Aerial Vehicle
论文作者
论文摘要
无人驾驶飞机的准确定位对于下一代自动化任务至关重要。本文提出了对扩展的特殊欧几里得组的速度辅助姿势估计的最小能量过滤器。采用的方法利用了问题的外分组对称性，以将惯性测量单元（IMU）传感器输出与具有里程碑意义的测量结果结合到稳健且高性能的状态估计值中。我们提出了一个异步离散时间实现，以将高带宽IMU与较低的离散时间地标度测量融合到现实世界中的典型情况下。通过模拟证明了过滤器的性能。
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.
