David Tedaldi

University of Padua, University of Zurich

Papers

Total Citations

346

H-Index

About

David Tedaldi is a leading researcher in robotics and sensor technology, with key contributions to inertial measurement unit (IMU) calibration and neuromorphic vision systems. His most influential work, "A robust and easy to implement method for IMU calibration without external equipments" (2014, 243 citations), revolutionized how low-cost MEMS-based IMUs are calibrated for robotics navigation and mapping tasks. By eliminating the need for expensive external equipment, Tedaldi made precise sensor calibration accessible to a broader research community, enabling more accurate localization and motion tracking in autonomous systems. His second highly cited paper, "Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)" (2016, 103 citations), addresses a critical limitation of standard cameras—the blind time between frames. Tedaldi’s work on event-based vision sensors provides high-frequency measurement updates, essential for high-speed robotic applications where continuous visual feedback is vital. Together, these contributions have established Tedaldi as a key figure in advancing both sensor calibration methodologies and real-time vision processing, with his methods widely adopted in robotics, autonomous vehicles, and embedded systems research.