AI Seminar

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

Domitilla Del VecchioAssistant ProfessorEECS

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