An Artificial Intelligence-Controlled Robotic System for Intelligence and ReconnUIssance Operations

VJ02010036
Description

The project has been designed to investigate drone swarms flying in coordination with terrestrial robots. The research will focus on diverse relevant means, problems, and activities, such as UI algorithms to reconfigure a drone swarm; object detection and classification; sensor-based data analysis and evaluation; and modeling robotic systems to define the limit parameters, criteria, and objective functions that optimize the trajectories of the elements of a concrete system. The obtained knowledge and adopted methods, instruments, and technologies will enable us to create a demonstrator of an adaptable drone swarm collaborating with terrestrial robots. The outputs will be applicable in, for example, CBRN operations, personal detection, and perimeter search.

Other people involved in the solution:

Gábrlík Petr, Ing., Ph.D.
Janoušek Jiří, Ing. 
Kadlec Radim, Ing., Ph.D. 
Mikulka Jan, doc. Ing., Ph.D. 
Pintér Marco, Bc. 
Procházka Martin 
Raichl Petr, Ing. 
Szabó Zoltán, Ing., Ph.D. 
Klouda Jan, Bc. 
Žalud Luděk, prof. Ing., Ph.D. - spoluřešitel

 

 

The research is carried out in the Laboratory of Unmanned Aerial Vehicles and Sensors

Information letter

 

uars

Keywords
autonomous drone
drone
CBRN
advanced sensors
artificial intelligence
flight parameters
reconnaissance
Project type
Applied research
Research partners

unob  ačr

University of Defense - Faculty of Military Technologies Brno - Prof. Dr. Ing. Alexander Štefek

Application guarantor: Army of the Czech Republic

BUT - FEKT - Institute of Automation and Measuring Technology - Prof. Ing. Luděk Žalud, Ph.D.

Main results

 JANOUŠEK, J.; SEMERÁD, J. Fusion of sensors for autonomous UAV Navigation. In PROCEEDINGS II OF THE 28TH STUDENT EEICT 2022 Selected Papers. 1. Brno: Vysoké učení technické v Brně, Fakulta elektrotechniky a komunikačních technologií, 2022. p. 63-66. ISBN: 978-80-214-6030-0.

CIHLÁŘ, M.; RAICHL, P.; GÁBRLÍK, P.; JANOUŠEK, J.; MARCOŇ, P.; ŽALUD, L.; LÁZNA, T.; MICHENKA, K.; NOHEL, J; a A Štefek. Simulation of Autonomous Robotic System for Intelligence and Reconnaissance Operations. In proc. of MESAS 2022.

STODOLA, Petr; NOHEL, Jan. Adaptive Ant Colony Optimization with Node Clustering for the Multi-Depot Vehicle Routing Problem. IEEE Transactions on Evolutionary Computation. ISSN 1089-778X. Přijato k publikování, vyjde v roce 2023.