Smart Devices and Autonomous Systems

Description

Study of Bayesian Estimation – Sensor Data Fusion. Gaussian Estimators: Kalman Filter. Extended Kalman Filter (EKF). Data Fusion. Application to robot’s Localization and Mapping. Case of study: SLAM (Simultaneous Localization and Mapping). Examples: object transportation, formation-flying, area coverage, platooning. Communications. Cooperative object localization. Cooperative task allocation, planning and coordination. Hybrid system models of architectures. Abdicable applications.

Program

M.Eng. in Electrical and Control Engineering

Objectives

• The student should be able to:  have the knowledge of Autonomous and smart systems, sensor and data fusion, Kalman filters, Localization and mapping, different methods of statistical calculations.