edX
MOOC / Non-credit
0
Self-Driving Cars with Duckietown
About this course
You’ll assemble a scaled‑down autonomous vehicle called a Duckiebot, wire its sensors and motors, and write code that lets it navigate a miniature city model. The hands‑on work walks you through perception, localization and control pipelines using tools like Python and ROS. By the end you’ll have a functioning self‑driving robot that can follow lanes and avoid obstacles on its own.
C
59/100
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- What the provider tells you
- 31/45
- Who stands behind it
- 20/35
- How complete the listing is
- 8/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- assemble and hardware‑wire a Duckiebot robot
- write perception and control software for autonomous navigation
- apply computer‑vision techniques to detect lanes and signs
- integrate sensor data for real‑time localization
- test and debug autonomous behavior in a scaled city environment
Course objectives
- understand the robotics stack from hardware to software
- learn to implement vision‑based lane following and obstacle avoidance
- gain practical experience with ROS and Python in a real robot
Artificial Intelligence
#machine learning
#problem solving
#computer vision
#control systems
#programming
#ai
#robotics
#autonomous driving
#simulations
#duckiebot
#ROS
#python
#lane detection
#PID control
#sensor fusion
#embedded systems
#autonomous navigation
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