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:
