System for deployment of groups of unmanned micro aerial vehicles in GPS-denied environments using onboard visual relative localization

A complex system for control of swarms of micro aerial vehicles (MAV), in literature also called as unmanned aerial vehicles (UAV) or unmanned aerial systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possi...

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Bibliographic Details
Published in:Autonomous robots 2017-04, Vol.41 (4), p.919-944
Main Authors: Saska, Martin, Baca, Tomas, Thomas, Justin, Chudoba, Jan, Preucil, Libor, Krajnik, Tomas, Faigl, Jan, Loianno, Giuseppe, Kumar, Vijay
Format: Article
Language:English
Subjects:
Aerospace industry
Artificial Intelligence
Complex systems
Computer Imaging
Control
Engineering
Global positioning systems
GPS
Indoor environments
Localization
Mechatronics
Micro air vehicles (MAV)
Motion planning
Pattern Recognition and Graphics
Robotics
Robotics and Automation
Satellite navigation systems
Stabilization
Trajectory planning
Unmanned aerial vehicles
Vision
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Summary:A complex system for control of swarms of micro aerial vehicles (MAV), in literature also called as unmanned aerial vehicles (UAV) or unmanned aerial systems (UAS), stabilized via an onboard visual relative localization is described in this paper. The main purpose of this work is to verify the possibility of self-stabilization of multi-MAV groups without an external global positioning system. This approach enables the deployment of MAV swarms outside laboratory conditions, and it may be considered an enabling technique for utilizing fleets of MAVs in real-world scenarios. The proposed visual-based stabilization approach has been designed for numerous different multi-UAV robotic applications (leader-follower UAV formation stabilization, UAV swarm stabilization and deployment in surveillance scenarios, cooperative UAV sensory measurement) in this paper. Deployment of the system in real-world scenarios truthfully verifies its operational constraints, given by limited onboard sensing suites and processing capabilities. The performance of the presented approach (MAV control, motion planning, MAV stabilization, and trajectory planning) in multi-MAV applications has been validated by experimental results in indoor as well as in challenging outdoor environments (e.g., in windy conditions and in a former pit mine).
ISSN:0929-5593
1573-7527
DOI:10.1007/s10514-016-9567-z