Papers
7
Total Citations
137
H-Index
5
About
Mario Sassano’s research lies at the intersection of multi-agent systems, game theory, and autonomous control, with a particular focus on collision avoidance and formation control for wheeled mobile robots. His most influential work, “Autonomous collision avoidance for wheeled mobile robots using a differential game approach” (49 citations), introduces a game-theoretic framework that models robots as rational agents in a non-cooperative setting, enabling decentralized, real-time collision avoidance. Building on this, his hybrid controller design (48 citations) addresses the practical challenges of online implementation, bridging the gap between theoretical local solutions and real-world deployment. Sassano has also made significant contributions to dynamic game theory, developing iterative and data-driven algorithms for computing Nash equilibria in linear quadratic discrete-time games—a foundational tool for multi-agent decision-making. His work on path planning and formation control integrates obstacle avoidance with coordinated motion, advancing the state of the art in autonomous navigation. With over 130 total citations, Sassano’s research is distinguished by its rigorous mathematical foundation and direct applicability to robotics, making him a key figure in the development of safe, scalable multi-agent systems.
Research Focus
Key Achievements
Top Papers
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- 4Path planning in formation and collision avoidance for multi-agent systems12 citations · 2022
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- 6Patrolling and collision avoidance beyond classical Navigation Functions4 citations · 2018
- 7Towards Spline-based Dynamic Input Allocation3 citations · 2023