Research focus: Computer vision, Deep learning, Robotic automation
As a researcher at RICAIP Testbed Prague, I focus on bridging industrial automation challenges with robotics and computer vision —specifically developing scalable perception systems for robotic manipulation. My work focuses on machine perception frameworks that combine geometric reasoning with deep learning methodologies to enable precise automated robotic handling. A key aspect of my approach is translating state-of-the-art, academic insights into practical tools for flexible manufacturing, ensuring solutions remain adaptable to diverse industrial needs.
What drives your passion for applied research?
My fascination with applied research comes from a curiosity about the link between abstract ideas and practical reality. It’s not just about theoretical constructs; it’s about building systems that do something in the real world. Take, for example, the challenge of enabling robots to see and manipulate objects. Replicating human perception and motor control in robots presents a monumental challenge, requiring innovative algorithmic approaches. This bridge between theory and practice — a bridge that empowers factories in the era of Industry 4.0 — is what motivates me.
The work is multidisciplinary by nature. One moment I’m wrestling with the nuances of a novel loss function, the next I’m debugging a simulation-to-reality transfer problem, and then I’m considering the practical constraints of deploying a perception pipeline on an embedded system controlling a heavy-lifting robotic arm. I find myself constantly learning, not just about the latest advances in deep learning or computer vision, but also about the underlying physics of epipolar geometry and image formation, the mechanics of robotic manipulation, and even the economics of industrial automation.
The rapid pace of technological advancement in this field is also a major motivator. Working with cutting-edge systems, some of which have only recently become available, is incredibly exciting. It demands constant learning and a willingness to grapple with complex systems. I believe that a deep understanding of any complex technology requires investigating into its historical roots, understanding the ingenious yet simple building blocks that have led to its current form. Only then can we truly contribute meaningfully to the field. Each project, therefore, becomes a unique and exciting journey of discovery, a journey that I find incredibly rewarding.
How has the RICAIP project shaped your work?
RICAIP has been transformative for my work, allowing me to move beyond isolated lab experiments and develop solutions with real-world impact. And it’s not just about the funding. Connecting our testbed with RICAIP partners across Europe has shown me the power of shared, cross-border testing to accelerate innovation. But even more importantly, it’s the human connection—the network of engineers and researchers co-designing solutions for SMEs that wouldn’t otherwise have access to dedicated R&D resources. This resonates with my own belief that innovative systems should be accessible, not locked behind proprietary walls. RICAIP facilitates this for applied research, strengthening not only CIIRC’s capabilities and those of its partners, but also contributing to the overall competitiveness of the European Union
