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AI Seminar

State Estimation and Control in Multi-Agent Decision and Control Systems

Domitilla Del VecchioAssistant ProfessorEECS
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In this talk, we consider the problem of state estimation and control for systems characterized by both continuous and logic evolution. In particular, multi-agent systems are considered such as multi-robot systems. In these systems, the continuous variables represent physical quantities such as the position and velocity of a robot, while discrete variables may represent the state of the logical system that is used for control and coordination. This work proposes a novel approach to state estimation and control that exploits partial order theory to overcome some of the severe complexity issues that arise in multi-agent systems. A multi-robot example involving two teams of robots competing against each other in a capture-the-flag like game is
proposed to illustrate the basic ideas.

Sponsored by

Toyota AI Lab Seminar