Tuesday, 3 April 2012

Programming a Robotic Car

In the last few weeks I have been quite busy following the course "Programming a Robotic Car" on Udacitity. The course is quite demanding because it force you to implement all the algorithms presented. I think this is by far the most effective way to really learn and their on-line platform based on Python works pretty well.

These are some of the problems that can be solved with the techniques explained:

  • Localizing a robot in a map
    • Monte Carlo Localization
    • Particle Filters Localization
  • Tracking objects
    • Kalman Filters
  • Motion planning
    • A Star
    • Dynamic Programming
  • Robot Motion
    • Smoothing
    • PID Control
  • Simultaneous localization and mapping
    • SLAM
    • Online SLAM
You can access all the code in my public repository under the following path:
  • Udacity >> CS 373 - Programming a robotic car
Here few snippets of the most relevant code. 

Kalman Filter:

Particle Filter:

A Start:


PID Control:

Twiddle (used for tuning the PID control parameters):

Online SLAM:

No comments:

Post a Comment

What you think about this post? I really appreciate your constructive feedback (positive and negative) and I am looking forward to start a discussion with you on this topic.