Marko Bertogna

Papers

Total Citations

H-Index

About

Marko Bertogna is a leading researcher at the intersection of computer vision and robotics, with a primary focus on 6 Degrees-of-Freedom (6D) pose estimation for autonomous systems. His work tackles the critical challenge of enabling machines to perceive and interact with their environment, particularly in demanding industrial and underwater settings. Bertogna has made significant contributions by developing deep learning-based solutions for industrial pick-and-place operations, addressing the complex task of object detection and pose estimation that remains a bottleneck in automation. His research extends to underwater robotics, where he has pioneered model-based approaches for 6D pose estimation from RGB imagery, overcoming the unique difficulties of limited visibility and light scattering in aquatic environments. With his most cited paper accumulating 11 citations, Bertogna’s work is gaining traction in the robotics community. He has also conducted benchmark analyses comparing data-driven and geometric methods for robot ego-motion estimation, providing valuable insights for the field. His research is particularly notable for bridging the gap between theoretical computer vision and practical robotic applications, offering solutions that are both robust and deployable in real-world scenarios.