Thesis Seminar: State Estimation in Multi-Agent Decision and Control Systems

Domitilla Del Vecchio, Control and Dynamical Systems, Caltech

We consider the problem of estimating the system state in a class of multi-agent decision and control systems. The talk focuses on the case in which the continuous state is available for measurement and the discrete state (or mode) of the system needs to be estimated. This scenario has practical interest, for example, in the case of decentralized 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 the estimation of discrete variables using partial order theory that overcomes some of the severe complexity issues that arise in multi-agent systems. The state estimator is then constructed for a multi-robot system involving two teams competing against each others. A final application example shows possible ways to extend the proposed state estimation approach to the context of monitoring distributed environments.