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About

Stefano Caselli is a prominent Italian robotics researcher whose work spans robot programming by demonstration, grasp planning, human-robot interaction, and autonomous systems. He has made foundational contributions to teaching robots through human demonstration, pioneering virtual reality-based frameworks that enable intuitive robot programming and grasp recognition — work that has collectively garnered hundreds of citations and remains influential in the field. Caselli's early research established robust methods for trajectory learning and approximation, with his 2006 paper on the topic accumulating 118 citations, while his virtual environment-based programming system (2004, 88 citations) helped define how simulation could bridge human intent and robotic execution. His investigations into grasp recognition using contact point analysis and 3D shape segmentation further advanced robot manipulation capabilities, enabling part-based grasping strategies grounded in human demonstration. Beyond manipulation, Caselli has contributed meaningfully to human-robot collaboration, developing comfort-aware object handover systems (2012, 69 citations) and affordance-sensitive interaction frameworks. His work extends into autonomous navigation through LIDAR-based keypoint features and real-time control systems for managing sensor-heavy robotic platforms. His leadership in the Italian MARIS project underscores his commitment to cutting-edge underwater intervention robotics, reflecting a career dedicated to advancing autonomous systems across diverse and challenging environments.