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:

Smoothing:


PID Control:


Twiddle (used for tuning the PID control parameters):


Online SLAM:



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