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Self-Driving Cars with Duckietown

The first robotics and AI MOOC with scale-model self-driving cars. Learn state-of-the-art autonomy with your own real robot (Duckiebot).

Este curso está archivado
14 semanas estimadas
2–4 horas por semana
Al ritmo del instructor
Con un cronograma específico
Gratis
Verificación opcional disponible

Sobre este curso

Omitir Sobre este curso

Autonomy and AI are all around us, revolutionizing our daily lives. Autonomous vehicles have a huge potential to impact society in the near future. Have you ever wondered how autonomous vehicles really work?

With this course, you will start from a box of parts and finish with a scaled self-driving car that drives autonomously in your living room. In the process, you will use state-of-the-art approaches, the latest software tools and real hardware in an engaging hands-on learning experience.

Self-driving cars with Duckietown is a practical introduction to vehicle autonomy. It explores real-world solutions to the theoretical challenges of automation, including their implementation in algorithms and their deployment in simulation as well as on hardware. Using modern software architectures built with Python, Robot Operating System (ROS) and Docker, you will appreciate the complementary strengths of classical architectures and modern machine learning-based approaches. The scope of this introductory course is to go from zero to having a self-driving car safely driving on a road.

This course is presented by Professors and Scientists who are passionate about robotics and accessible education. It uses the Duckietown robotic ecosystem, an open-source platform created at the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and now used in over 80 universities worldwide.

We support a track for students to deploy their solutions in a simulation environment and an option for learners to engage in the tangible, hands-on learning experience by procuring a low-cost Jetson Nano-powered Duckiebot kit, e.g., from here.

This course is made possible thanks to the support of the Swiss Federal Institute of Technology in Zurich (ETH Zurich), in collaboration with the University of Montreal (Prof. Liam Paull), the Duckietown Foundation, and the Toyota Technological Institute at Chicago (Prof. Matthew Walter).

Curso creado con el apoyo de

University of MontrealDuckietown FoundationToyota Technological Institute at Chicago

De un vistazo

  • Idioma: English
  • Transcripción de video: English

Lo que aprenderás

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After this course you will be able to program your Duckiebots to navigate (without accidents!) in road lanes of a model city with rubber-duckies-pedestrians-obstacles using predominantly computer vision based techniques. Moreover, you will:

  • recognize essential robot subsystems (sensing, actuation, computation, memory, mechanical) and describe their functions

  • make your Duckiebot drive in arbitrary user-specified paths

  • understand how to command a robot to reach a goal position

  • make your Duckiebot do autonomous decision making according to "traditional approaches" (estimation, planning, control)

  • make your Duckiebot do autonomous decision making according to "modern approaches" (imitation learning, reinforcement learning, deep learning)

  • process streams of images

  • be able to set up an efficient software environment for robotics with state of the art tools (Docker, ROS, Python)

  • program your Duckiebot and make it safely drive in empty roads lanes

  • program your Duckiebot and make it recognize obstacles such as rubber duckies

  • program your Duckiebot and make it avoid obstacles such as rubber duckies

  • program your Duckiebot and make it safely drive down roads with pedestrian duckies

Additional goals (require hardware)

  • independently assemble a Duckiebot and a Duckietown

  • remotely operate your Duckiebot and see with its eye(s)

  • be able to discuss differences between theory, simulation and real word implementation for different approaches

Acerca de los instructores

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

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