Daniele Marzorati

University of Milan, Politecnico di Milano, University of Milano-Bicocca

Papers

Total Citations

163

H-Index

About

Daniele Marzorati is a leading researcher in robotics and autonomous navigation, whose work has fundamentally advanced the field of Simultaneous Localization and Mapping (SLAM). His primary research areas include multi-sensor fusion, 3D vision, and probabilistic robotics, with a particular focus on enabling robots to build maps and localize themselves in complex, real-world environments. Marzorati’s most impactful contribution is the "Rawseeds ground truth collection systems for indoor self-localization and mapping" (2009), which has garnered 138 citations and remains a benchmark for evaluating SLAM algorithms. This work provided the robotics community with a standardized, high-fidelity dataset that has been essential for validating new approaches to indoor navigation. He has also pioneered innovative techniques for integrating 3D lines and points in 6DoF visual SLAM using uncertain projective geometry, offering a seamless framework for fusing data from heterogeneous sensors. His research on particle-based sensor modeling for 3D-vision SLAM and single/multi-camera systems using the Extended Kalman Filter has further pushed the boundaries of vision-based navigation. Marzorati’s work is distinguished by its rigorous mathematical foundation and practical applicability, making him a key figure in the development of robust, vision-centric SLAM systems for consumer-level robotics.