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Intersections of AI and autonomous robotic systems ↓

The robotic division consists of the Computational Robotics Laboratory (CRL) and Chronorobotics Laboratory. In both of them, we perform fundamental and applied research at the intersections of artificial intelligence and autonomous robotic systems. We are seeking unique solutions to address real-world challenges to improve the quality of life and to understand principles emerging in nature.

Computational Robotics

In the Computational Robotics Lab, we focus on computational approaches and methodologies applied to address challenging problems arising from robotic information gathering. Beside traditional computational approaches based on state-space search techniques and combinatorial optimization, we also work on approaches originated in nature-inspired algorithms. Approaches that can be applied to address complex real-world problems that are not well-posed mathematically.  These include computational intelligence and soft-computing techniques such as artificial neural networks, swarm intelligence, evolutionary computation, or reaction diffusion processes. We work on designing new scalable algorithms and computational models enabling application and improving capabilities of collective robotic systems to operate in dynamic, unstructured environments with imperfect sensing and perception.

The newest member of our robofamily


The Chronorobotics Lab focuses on the development of robotic technologies which will lead to the possibility of long-term deployment of autonomous robots in human inhabited areas. The primary emphasis of our research is on the comfort of the people who use new robotic technologies and on ensuring that the technologies do not disrupt human environments. In our view, humans are the top priority and robots are only machines that are supposed to help people in non-invasive ways. We consider it unacceptable to maximize the utility of robots at the expense of the comfort of their users.



EU-funded Horizon project combining micro-robotic, biological and machine learning technologies to support the well-being of honeybee queens.

Active Environment Modeling With Mobile Robots

Active Environment Modeling With Mobile Robots

Autonomous mobile robots can carry out tasks in environments that are unsafe or otherwise unsuitable for humans. The robots' missions in such environments range from remote facilities inspections to searching for survivors in the collapsed buildings or caves. Our models were also deployed on a tracked robot during the DARPA Subterranean Challenge.

Research Results

human future

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