Max Robotics — Global Service Robot Directory + US Certification

About

Luca Bogoni’s research lies at the intersection of robotics, artificial intelligence, and functional object recognition, with a particular focus on how machines can understand and interact with tools based on their purpose rather than just their shape. His work pioneered the concept of “functionality” in robotic systems—moving beyond static geometric representations to develop active, performatory approaches that allow robots to infer an object’s function through direct interaction and sensor feedback. In his most cited paper (21 citations), Bogoni introduced a discrete events systems framework for modeling behaviors and tasks across heterogeneous robotic agents, enabling more adaptive and coordinated multi-robot control. His earlier foundational work on functionality characterization (9 citations) emphasized how robots can recover functional properties by manipulating tools and observing outcomes, such as chopping or piercing operations. Through a series of papers exploring specific functional features—from chopping to piercing—Bogoni demonstrated that robots could learn to recognize and apply tools by analyzing the interaction between tool and target. His contributions remain influential for researchers working on affordance-based robotics, autonomous manipulation, and task-oriented perception.