Bio-inspired Infrastructure-free relative localization and its multi-agent applications

Abstract

Relative localization is an essential part of autonomous multi-agent systems. In this study, drawing inspiration from animals that achieve collective behaviors solely through individual perception of relative information, we propose an infrastructure-free distributed relative localization framework mainly utilizing onboard ranging sensors. In 2D scenarios, we start with system modeling, based on which optimal sensor configuration and algorithm design are conducted. Subsequently, we perform a thorough performance analysis and validate the overall system design through field tests using unmanned ground vehicles (UGVs) equipped with ultra-wideband (UWB) ranging sensors and micro-controller units onboard. In 3D scenarios, similarly, we followed the 2D procedures and then analyzed the performances of the proposed methods in 3D scenarios. Then a UGV leader-follower and UGV flocking control are conducted to show the effectiveness of the proposed relative localization framework in real autonomous vehicle platforms. A heterogeneous extension of the flocking control is then delivered. We then provide the outlook for potential future developments and further practical applications. Contributions include the following: the geometric dilution of precision (GDOP) and Cramér-Rao lower bound (CRLB) are derived; a novel Euclidean distance matrix (EDM)-based trilateration algorithm and a maximum likelihood estimation algorithm are proposed; the computational complexities of the proposed algorithms are compared with the state-of-the-art methods; comprehensive simulation and field tests are delivered to verify the efficiency and effectiveness; and multi-UGV experiments are conducted to validate the viability and applicability of the proposed framework for autonomous multi-UGV platforms and collaborative unmanned vehicle (UXV) applications. The theoretical, numerical, and experimental results will shed light on the design and optimization of infrastructure-free relative localization systems. The contributions also lie in advancing UXV technology and paving the way for innovative and impactful applications in the future.

Date of Award	2024
Original language	English
Awarding Institution	The Hong Kong University of Science and Technology
Supervisor	Li QIU (Supervisor)