DocumentCode
720504
Title
MAV-swarms: Unmanned aerial vehicles stabilized along a given path using onboard relative localization
Author
Saska, Martin
Author_Institution
Dept. of Cybern., Czech Tech. Univ. in Prague, Prague, Czech Republic
fYear
2015
fDate
9-12 June 2015
Firstpage
894
Lastpage
903
Abstract
A novel approach for stabilization and navigation of swarms of Micro Aerial Vehicles (MAVs) along a predefined path through a complex environment with obstacles is introduced in this paper. The method enables to control large MAV swarms (in literature also called UAV swarms) based only on onboard sensors and without any inter-vehicle communication. The proposed method relies on visual localization modules carried by all MAVs, which provide estimation of the relative positions of neighbours in the swarm. Guess on the positions of the neighbouring MAVs and information on the relative positions of obstacles are integrated into swarm stabilization via Reynolds´ Boids model. The performance of the complex system is shown in various numerical simulations and in experiments with a fleet of MAVs in the paper. Presented experimental results with the multi-MAV swarm were conducted in indoor and outdoor environment, and without using any external global localization system such as Vicon motion capture system or GPS localization.
Keywords
aerospace navigation; autonomous aerial vehicles; indoor environment; large-scale systems; mobile robots; multi-robot systems; stability; swarm intelligence; MAV navigation; Reynolds´ Boids model; UAV swarms; complex system; indoor environment; microaerial vehicles; multiMAV swarm; onboard relative localization; onboard sensors; outdoor environment; relative position estimation; stabilization; unmanned aerial vehicles; visual localization modules; Collision avoidance; Force; Navigation; Robots; Shape; Vehicles; Visualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Unmanned Aircraft Systems (ICUAS), 2015 International Conference on
Conference_Location
Denver, CO
Print_ISBN
978-1-4799-6009-5
Type
conf
DOI
10.1109/ICUAS.2015.7152376
Filename
7152376
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