Unmanned Aircraft and Sensor Systems Laboratory

The primary activity of the research laboratory is remote sensing using unmanned aerial vehicles (UAVs) and the subsequent analysis of acquired data for applications in precision agriculture, cartography, and geography. Multispectral and thermal imaging are used to generate maps, plans, and 3D models. UAVs are also employed for magnetic field measurements and atmospheric chemical sensing.

The laboratory is further engaged in the development of flight control software for autonomous navigation based on computer vision, as well as the development of counter-UAV technologies. In addition, we develop artificial intelligence algorithms for swarm flight and cooperative control of multiple unmanned aerial systems.

Office: SC3.83

Contact persons:

• Assoc. Prof. Petr Marcoň, Ph.D. – marcon@vut.cz
• Jiří Janoušek, Ph.D. – jiri.janousek@vut.cz

UAV Research Centre at Brno University of Technology: BUT DRONE RESEARCH CENTER

Current Research Projects

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

This project focuses on research into cooperative UAV swarm operations in collaboration with unmanned ground vehicles (UGVs). The research addresses several areas, including artificial intelligence algorithms for dynamic swarm reconfiguration, object detection and classification, and analysis of data collected from advanced sensors.

Based on the acquired knowledge, methodologies, tools, and technologies, a demonstrator of an adaptive UAV swarm cooperating with ground robots will be developed. The resulting system is intended for a wide range of applications, including CBRN operations, search and rescue, intelligence, surveillance, and reconnaissance (ISR) missions.

Autonomous UAV with a Multisensor Stabilized Gimbal and Artificial Intelligence

The objective of this project is to develop an autonomous UAV equipped with a multisensor stabilized gimbal integrating an onboard processor capable of real-time image processing and artificial intelligence.

The UAV position will be continuously corrected using metadata generated by the multisensor payload, enabling motion estimation even in the absence of conventional navigation sensors such as GNSS. This approach significantly improves operational capability in GNSS-denied environments.

Interface for Intuitive and Reliable Control of Heterogeneous Robot Teams with Health Monitoring and Fault Management
This project focuses on research and development of technologies for collecting, integrating, and visualizing telemetry from large teams of predominantly aerial robotic systems. It also addresses efficient mission planning and real-time visualization of sensor data for operators.

The resulting interface will provide interactive multi-robot mission planning together with autonomous responses to failures occurring at different levels of the robotic system. The interface is designed to enable effective operation by users without specialized robotics training.
 

Pokročilý systém družicové komunikace a bezpilotních letadel pro autonomní řízení v zarušeném prostředí.
This project develops technologies enabling reliable command, control, and coordination of autonomous systems operating in environments affected by severe electromagnetic interference, where both GNSS navigation and conventional communication links are degraded or unavailable.

The primary objective is to create a secure satellite-based communication infrastructure for data exchange between the command system and various UAV platforms. The infrastructure will provide a resilient and adaptive communication link ensuring reliable operation under critical conditions where conventional communication systems fail.
 

Multi-Robot System for Autonomous Field Operations with Multi-Source Navigation
This project builds upon the previous project AI-Driven Robotic System for Intelligence, Surveillance and Reconnaissance Missions, whose objective was to develop a demonstrator of a heterogeneous robotic team capable of autonomous reconnaissance and surveillance.

The developed system enables efficient acquisition of intelligence data and its transmission to command centres, supporting situational awareness and the creation of a common operational picture. The new project extends these capabilities through advanced multi-source navigation and improved autonomy for operation in challenging environments.

Courses - FEKT-BPC-BPL – Unmanned Aircraft

The course provides a comprehensive introduction to unmanned aircraft systems, covering both theoretical foundations and practical flight training. Students gain knowledge of UAV technologies, flight principles, regulations, and operational procedures, followed by practical exercises including flight operations and formation flying.

More information is available in the course description.