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UAV-UGV Collaborative Localisation with Minimum Sensing
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DOI：10.3390/s24144629.png)
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Abstract
En 中文
This paper presents a novel methodology to localise Unmanned Ground Vehicles (UGVs) using Unmanned Aerial Vehicles (UAVs). The UGVs are assumed to be operating in a Global Navigation Satellite System (GNSS)-denied environment. The localisation of the ground vehicles is achieved using UAVs that have full access to the GNSS. The UAVs use range sensors to localise the UGV. One of the major requirements is to use the minimum number of UAVs, which is two UAVs in this paper. Using only two UAVs leads to a significant complication that results an estimation unobservability under certain circumstances. As a solution to the unobservability problem, the main contribution of this paper is to present a methodology to treat the unobservability problem. A Constrained Extended Kalman Filter (CEKF)-based solution, which uses novel kinematics and heuristics-based constraints, is presented. The proposed methodology has been assessed based on the stochastic observability using the Posterior Cram & eacute;r-Rao Bound (PCRB), and the results demonstrate the successful operation of the proposed localisation method.
Keywords:
constrained Kalman Filter
posterior Cram & eacute
r-Rao bound
UAV-UGV collaboration
GNSS denied localisation
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