Antonio Bono

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About

Antonio Bono is a researcher whose work bridges multiagent systems, model predictive control (MPC), and human-robot interaction (HRI). His key contributions lie in developing distributed control strategies for teams of unmanned vehicles, where he solves the reference tracking problem under formation constraints using a novel kinematic description of swarm agents. This work, published in 2022, has garnered 17 citations, reflecting its impact on autonomous coordination. Bono also advances HRI through the Open Access NAO (OAN) framework, a ROS2-based software platform for the NAO robot. Released in 2024, OAN addresses the demand for improved performance and new features in HRI experimentation, enabling researchers to leverage ROS2’s capabilities for more sophisticated interactions. By combining theoretical rigor in control theory with practical software tools, Bono’s research facilitates real-world applications in robotics, from swarm formation flying to social robotics. His work is notable for its emphasis on open-access tools and distributed algorithms, making it accessible and impactful for students and researchers exploring autonomous systems and human-robot collaboration.