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About

Michal Havlena is a researcher whose work lies at the intersection of computer vision, robotics, and medical imaging. His most significant contribution is a groundbreaking method for hand-eye calibration, published in 2011, which has garnered 46 citations. This work addresses a critical challenge: performing calibration without a physical calibration target by leveraging Structure-from-Motion to recover camera poses up to scaling, using L∞ minimization for robust optimization—a technique essential for applications where traditional targets are impractical. Havlena’s impact extends into robotics, where he has advanced localization and navigation for humanoid robots like the Nao, fusing odometry with visual sensor data to enable autonomous movement and obstacle avoidance. In the medical domain, he has contributed to robot-assisted eye surgery through 3D reconstruction of the retinal surface, demonstrating the versatility of his vision-based approaches. With a focus on practical, real-world solutions, Havlena’s work bridges theoretical rigor and applied robotics, offering valuable insights for students and researchers in autonomous systems and surgical robotics.