Danilo Saccani
Politecnico di Milano, École Polytechnique Fédérale de Lausanne
Papers
2
Total Citations
15
H-Index
2
About
Danilo Saccani is a researcher advancing the frontier of cooperative multi-agent robotic systems, with a primary focus on distributed model predictive control (MPC) and networked control under communication constraints. His work addresses critical challenges in coordinating robot swarms for applications like search and rescue, hazardous environment operations, and environmental monitoring. Saccani’s major contributions include developing novel MPC frameworks that ensure safety-critical constraints are met even when agents face limited communication and time-varying network topologies—a persistent challenge in real-world deployments. His 2023 paper on multi-agent distributed MPC with connectivity constraints has garnered 11 citations, reflecting its impact on the field. In related work, he tackles the open problem of controller reconfiguration when agents join or leave a network, proposing solutions that maintain operational constraints dependent on individual agent behavior. Saccani’s research is particularly notable for bridging theoretical control theory with practical mobile robot swarm applications, offering scalable and robust coordination strategies. His achievements are shaping the next generation of autonomous systems that must operate reliably under dynamic, communication-limited conditions.
Research Focus
Key Achievements
Top Papers
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- 2