Cooperative Navigation and Guidance of a Micro-Scale Aerial Vehicle by an Accompanying UAV using 3D LiDAR Relative Localization

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00359583" target="_blank" >RIV/68407700:21230/22:00359583 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/ICUAS54217.2022.9836116" target="_blank" >https://doi.org/10.1109/ICUAS54217.2022.9836116</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICUAS54217.2022.9836116" target="_blank" >10.1109/ICUAS54217.2022.9836116</a>

Result language

angličtina

Original language name

Cooperative Navigation and Guidance of a Micro-Scale Aerial Vehicle by an Accompanying UAV using 3D LiDAR Relative Localization

Original language description

A novel approach for cooperative navigation and guidance of a micro-scale aerial vehicle by an accompanying Unmanned Aerial Vehicle (UAV) using 3D Light Detection and Ranging (LiDAR) relative localization is proposed in this paper. The use of 3D LiDARs represents a reliable way of environment perception and robust UAV self-localization in Global Navigation Satellite System (GNSS)-denied environments. However, 3D LiDARs are relatively heavy and they need to be carried by large UAV platforms. On the contrary, visual cameras are cheap, light-weight, and therefore ideal for small UAVs. However, visual self-localization methods suffer from loss of precision in texture-less environments, scale unobservability during certain maneuvers, and long-term drift with respect to the global frame of reference. Nevertheless, a micro-scale camera-equipped UAV is ideal for complementing a 3D LiDAR-equipped UAV as it can reach places inaccessible to a large UAV platform. To gain the advantages of both navigation approaches, we propose a cooperative navigation and guidance architecture utilizing a large LiDAR-equipped UAV accompanied by a small secondary UAV carrying a significantly lighter monocular camera. The primary UAV is localized by a robust LiDAR Simultaneous Localization and Mapping (SLAM) algorithm, while the secondary UAV utilizes a Visual-Inertial Odometry (VIO) approach with lower precision and reliability. The LiDAR data are used for markerless relative localization between the UAVs to enable precise guidance of the secondary UAV in the frame of reference of the LiDAR SLAM. The performance of the proposed approach has been extensively verified in simulations and real-world experiments with the algorithms running onboard the UAVs with no external localization infrastructure.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

20204 - Robotics and automatic control

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

2022 International Conference on Unmanned Aircraft Systems (ICUAS)

ISBN

978-1-6654-0593-5

ISSN

2373-6720

e-ISSN

2575-7296

Number of pages

10

Pages from-to

526-535

Publisher name

IEEE Industrial Electronics Society

Place of publication

Piscataway

Event location

Dubrovnik

Event date

Jun 21, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000854030400062