A Minimum Energy Filter for Localisation of an Unmanned Aerial Vehicle
arXiv:2009.04630 · doi:10.1109/CDC42340.2020.9303730
Abstract
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.
To be presented at the 59th IEEE Conference on Decision and Control (CDC), 14-18 December 2020