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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Vision-controlled micro flying robots: from system design to autonomous navigation and mapping in GPS-denied environments
Organization Unit
Authors
  • Davide Scaramuzza
  • Michael C Achtelik
  • Lefteris Doitsidis
  • Friedrich Fraundorfer
  • Elias Kosmatopoulos
  • Agostino Martinelli
  • Markus W Achtelik
  • Margarita Chli
  • Savvas Chatzichristofis
  • Laurent Kneip
  • Daniel Gurdan
  • Lionel Heng
  • Gim Hee Lee
  • Simon Lynen
  • Lorenz Meier
  • Marc Pollefeys
  • Alessandro Renzaglia
  • Roland Siegwart
  • Jan Carsten Stumpf
  • Petri Tanskanen
  • Chiara Troiani
  • Stephan Weiss
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Journal Title IEEE Robotics and Automation Magazine
Publisher Institute of Electrical and Electronics Engineers
Geographical Reach international
ISSN 1070-9932
Volume 21
Number 3
Page Range 26 - 40
Date 2014
Abstract Text Autonomous microhelicopters will soon play a major role in tasks like search and rescue, environment monitoring, security surveillance, and inspection. If they are further realized in small scale, they can also be used in narrow outdoor and indoor environments and represent only a limited risk for people. However, for such operations, navigating based only on global positioning system (GPS) information is not sufficient. Fully autonomous operation in cities or other dense environments requires microhelicopters to fly at low altitudes, where GPS signals are often shadowed, or indoors and to actively explore unknown environments while avoiding collisions and creating maps. This involves a number of challenges on all levels of helicopter design, perception, actuation, control, and navigation, which still have to be solved. The Swarm of Micro Flying Robots (SFLY) project was a European Union-funded project with the goal of creating a swarm of vision-controlled microaerial vehicles (MAVs) capable of autonomous navigation, three-dimensional (3-D) mapping, and optimal surveillance coverage in GPS-denied environments. The SFLY MAVs do not rely on remote control, radio beacons, or motion-capture systems but can fly all by themselves using only a single onboard camera and an inertial measurement unit (IMU). This article describes the technical challenges that have been faced and the results achieved from hardware design and embedded programming to vision-based navigation and mapping, with an overview of how all the modules work and how they have been integrated into the final system. Code, data sets, and videos are publicly available to the robotics community. Experimental results demonstrating three MAVs navigating autonomously in an unknown GPS-denied environment and performing 3-D mapping and optimal surveillance coverage are presented.
Digital Object Identifier 10.1109/MRA.2014.2322295
Other Identification Number merlin-id:10217
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