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About

Fabrizio Bottarel is a robotics researcher whose work lies at the intersection of robotic manipulation, perception, and human-robot collaboration. His key contributions include developing rigorous benchmarking standards for robotic grasping, advancing 6D object pose tracking, and exploring the dynamics of safe human-robot interaction. Bottarel led the creation of GRASPA 1.0, a benchmark framework for robot arm grasping performance that has garnered 31 citations for establishing standardized protocols and metrics in a field previously lacking them. His MaskUKF algorithm (13 citations) innovatively combines deep instance segmentation with an Unscented Kalman Filter to achieve robust 6D object pose and velocity tracking—a critical capability for modern manipulation tasks. Bottarel has also investigated the integration of physical and social interaction cues to enhance human-robot collaboration, addressing both safety and usability. More recently, his work on confidence-guided shape completion (2022) tackles the challenge of incomplete 3D visual data in unstructured environments, promising to improve robotic perception for real-world applications. Through these contributions, Bottarel is helping to bridge the gap between controlled laboratory robotics and practical, real-world deployment.