doc. Ing. Tomáš Krajník, Ph.D.

Design and develop methods which will allow mobile robots to learn the structure of their operational environment, how it changes over time, and what are the reasons of the changes observed. Investigate the impact of these methods on the ability of the mobile robots to operate in changing, human-populated environments, on the efficiency of their operation and on their acceptance by the humans.

Autonomous navigation technology has progressed tremendously over the last years and driverless cars, autonomous harvesters, and industrial robots and now being deployed to structured and know environments. However, rescue and service robots need to be able to operate in unknown, unstructured, and changing environments. Moreover, the need for 24/7 operation times requires dealing with unexpected situations and adverse conditions. In other words, robots need to be persistent and demonstrate a high level of robustness and fault tolerance and recovery, and above all of that, they have to be able to adapt over time to the changes in their operational environment. The topic of this PhD is research and development of methods that allow mobile robots to achieve reliable autonomous operation in adverse conditions, and unstructured, unknown environments.

Advances in robotics enabled long-term deployment of autonomous robots that interact with the natural environment. To operate in natural environments effectively, unobtrusively, and safely, robots must understand the structure of the environment and how it changes over time. The dissertation aims to develop methods for building, refining, and updating models of environmental dynamics by robotic systems. The impact of the methods developed will be evaluated primarily through the interaction of the robots with biological systems.