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About

Giuseppe Fedele is a leading researcher in the field of multi-agent systems and autonomous robotics, with a particular focus on formation control, obstacle avoidance, and human-robot interaction. His most influential work, "Obstacles Avoidance Based on Switching Potential Functions" (2017), has garnered 37 citations and introduced a novel approach to navigating autonomous agents through dynamic environments. Fedele has made significant contributions to distributed control strategies, notably through his work on reference tracking for multi-agent systems using model predictive control (2022, 17 citations), where he developed a novel kinematic description enabling efficient formation-constrained coordination of unmanned vehicles. His research extends to the challenging problem of matching between multiple swarms (2024, 8 citations), with applications in transport and logistics. Demonstrating his commitment to practical robotics, Fedele also developed the Open Access NAO (OAN) framework (2024), a ROS2-based software architecture that enhances HRI experimentation with the NAO robot. His work on interpolation-based minimum-time control for linear systems further showcases his versatility in control theory. With a growing citation record and contributions spanning both theoretical foundations and accessible software tools, Fedele continues to advance the capabilities of autonomous systems.