Onboard Ranging-based Relative Localization and Stability for Lightweight Aerial Swarms

Journal Article (2025)
Author(s)

Shushuai Li (TU Delft - Control & Simulation)

Feng Shan (Southeast University)

Jiangpeng Liu (Southeast University)

Mario Coppola (TU Delft - Control & Simulation)

C de Wagter (TU Delft - Control & Simulation)

G. C. H. E. de Croon (TU Delft - Control & Simulation)

Research Group
Control & Simulation
DOI related publication
https://doi.org/10.1109/LRA.2025.3597039
More Info
expand_more
Publication Year
2025
Language
English
Research Group
Control & Simulation
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
10
Volume number
10
Pages (from-to)
10066-10073
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Lightweight aerial swarms have potential applications in scenarios where larger drones fail to operate efficiently. The primary foundation for lightweight aerial swarms is efficient relative localization, which enables cooperation and collision avoidance. Computing the real-time position is challenging due to extreme resource constraints. This letter presents an autonomous relative localization technique for lightweight aerial swarms without infrastructure by fusing ultra-wideband wireless distance measurements and the shared state information (e.g., velocity, yaw rate, height) from neighbors. This is the first fully autonomous, tiny, fast, and accurate relative localization scheme implemented on a team of 13 lightweight (33 grams) and resource-constrained (168 MHz MCU with 192 KB memory) aerial vehicles. The proposed resource-constrained swarm ranging protocol is scalable, and a surprising theoretical result is discovered: the unobservability poses no issues because the state drift leads to control actions that make the state observable again. By experiment, less than 0.2 m position error is achieved at the frequency of 16 Hz for as many as 13 drones. The code is open-sourced, and the proposed technique is relevant not only for tiny drones but can be readily applied to many other resource-restricted robots.

Files

License info not available
warning

File under embargo until 09-02-2026