Davide Todesca

Papers

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About

Davide Todesca is a researcher at the forefront of human-robot interaction and biomechanical simulation, with a primary focus on real-time human pose estimation and its integration into Human-In-The-Loop (HITL) dynamic systems. His most notable contribution is the development of a vision-based, marker-less system for real-time human pose measurement, as detailed in his highly cited 2025 paper (10 citations). This work enables the instantaneous evaluation of a user’s pose and inertial properties, allowing robotic platforms to be controlled intuitively based on human movement. The implications are profound for fields such as sports science, rehabilitation engineering, and advanced simulator design, where seamless human-machine collaboration is critical. By eliminating the need for physical markers, Todesca’s approach enhances the practicality and accessibility of HITL systems, bridging the gap between human biomechanics and robotic control. His research not only advances the state of the art in real-time sensing but also opens new avenues for adaptive, user-responsive technologies. With a growing citation impact, Todesca is establishing himself as a key innovator in the integration of computer vision and robotics for human-centered applications.