Teaching

AA 275: Navigation for Autonomous Systems

Navigation is a key element in many autonomous systems, from self-driving cars to flying robots. In this course you will learn about the technologies that enable autonomous navigation. Topics: navigational system design using GPS as an example; data-driven approach using machine learning and deep learning; model-based approach using probabilistic graph model; theory-based approach using formal verification; intelligent navigational sensor fusion; cyber security and integrity monitoring for localization and navigation.

Prerequisites: AA 228 or EE 278; and EE 263 or AA 212. Recommended: AA 272, EE 261, AA 273.

AA272: Global Positioning Systems

The principles of satellite navigation using Global Positioning Systems (GPS). Positioning techniques using code tracking, single and dual frequency, carrier aiding, and use of differential and assisted GPS/GNSS for improved accuracy and integrity. Students will learn the building blocks to go from raw received satellite time in nanoseconds all the way to a sophisticated position solution. Using provided Android smartphones, students will collect data and implement an open-ended course project where the goal is to get creative and solve an interesting problem using the tools developed in this course.

Prerequisites: familiarity with matrix algebra and MatLab (or another mathematical programming language).

AA173: Flight Mechanics & Controls

The basic equations of motion for aircraft, and the design of automatic control systems for them. Non-linear and linearized longitudinal and lateral dynamics; linearized aerodynamics; natural modes of motion; autopilot design to enhance stability and to control the flight path.

Prerequisites: E15, E105 and familiarity with Matlab.