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Martin Saska
presents
Our achievements towards swarms of autonomous unmanned vehicles in GPS denied environment.
 
On 2018-01-08 11:30 at E112
 
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 will be
presented. 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).
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).

Details of the presentation can be found in journal articles:

M Saska, T Baca, J Thomas, J Chudoba, L Preucil, T Krajnik, J Faigl, G Loianno
and V Kumar. System for deployment of groups of unmanned micro aerial vehicles
in GPS-denied environments using onboard visual relative localization.
Autonomous Robots, Volume 41, Issue 4, pp 919–944, 2017.
https://link.springer.com/article/10.1007/s10514-016-9567-z 

M Saska, V Vonásek, J Chudoba, J Thomas, G Loianno and V Kumar. Swarm
Distribution and Deployment for Cooperative Surveillance by Micro-Aerial
Vehicles. Journal of Intelligent & Robotic Systems. 84(1):469–492, December,
2016.
https://link.springer.com/article/10.1007/s10846-016-0338-z

J Chudoba, M Kulich, M Saska, T Báča and L Přeučil. Exploration and Mapping
Technique Suited for Visual-features Based Localization of MAVs. Journal of
Intelligent & Robotic Systems. 84(1):351-369, December, 2016.
https://link.springer.com/article/10.1007/s10846-016-0358-8
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