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UAV-UGV Collaborative Localisation with Minimum Sensing.
De Silva, A H T Eranga; Katupitiya, Jayantha.
Affiliation
  • De Silva AHTE; School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
  • Katupitiya J; School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW 2052, Australia.
Sensors (Basel) ; 24(14)2024 Jul 17.
Article in En | MEDLINE | ID: mdl-39066025
ABSTRACT
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 Cramér-Rao Bound (PCRB), and the results demonstrate the successful operation of the proposed localisation method.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2024 Document type: Article Affiliation country: Australia Country of publication: Suiza

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Sensors (Basel) Year: 2024 Document type: Article Affiliation country: Australia Country of publication: Suiza