Cooperative Localization of Multi-Agent Autonomous Aerial Vehicle (AAV) Networks in Intelligent Transportation Systems

Abstract

GNSS-independent localization is one of the most prominent research problems in aerial autonomous systems navigation, especially in certain applications where Simultaneous Localization and Mapping (SLAM) methods are inapplicable due to the complexity of the environment, or in open-air spaces where a flock of Autonomous Aerial Vehicles (AAVs) navigate in a GNSS-independent fashion. This paper introduces a filter through which AAVs form a multi-agent Cellular Vehicle-to-Everything (C-V2X) network to exchange their estimated positions, and eventually achieve a group consensus over the true position of each vehicle. The localization error correction takes place in the filter with reference to the AAV’s relative range from neighbouring vehicles, that is measured by onboard ranging devices. It is shown that in ideal situations where rangefinder errors can be neglected, cooperative localization yields perfect localization, if the network is sufficiently large and sufficiently connected. It is also shown that the accuracy of cooperative localization is superior to the existing least-mean-square-error based techniques, where a centralized controller augments the positioning accuracy of the flock. Cooperative localization is also favourable due to the fact that the process is computationally affordable and fully distributed. Theoretical derivations and results have been validated through case studies and Monte Carlo simulations, and suggest cooperative localization as a complementary navigation technique to odometery, and other advanced solutions that are available in the literature.