Autonomous Mobility on Demand systems based on self-driving cars will make a huge impact in the world. This class describes the basics of modeling, perception, learning, planning, and control for fleets of self-driving cars. We focus particular regard to the problem of integration and co-design of components and behaviors. The course has a heavy experimental component.
The students will learn how to create all parts of an architecture for a complex multi-robot system performing a nontrivial task (an autonomous taxi service).
Part 1: Single car functionalities (perception-planning-control loop, based on vision data); Part 2: Multiple cars (formal methods for safety, platooning, coordination, fleet-level policy optimization)
Course notes will be provided for free in an electronic form.
Course notes will be provided for free in an electronic form. These are some books that can be used to provide background information or consulted as references: (1) Siegwart, Nourbakhsh, Scaramuzza - Introduction to autonomous mobile robots; (2) Norvig, Russell - Artificial Intelligent, a modern approach. (3) Peter Corke - Robotics Vision and Control (4) Oussama Khatib, Bruno Siciliano - Handbook of Robotics
Prerequisites / Notice
This course is also known as Duckietown. Students should have taken a basic course in probability, and should be familiar with basic programming and Linux use.