March 1

Robot Localization using Montecarlo Localization

0  comments

The problem of localising a robot in a known environment is quite interesting. I would like to share with you my solution to the homework assignment for the unit 1 of the “CS 373 Programming a Robotic Car”.

The environment is a discrete map (colours matrix) where each area can be green or red. The robot can sense the colour (sense function) of the area where is currently on and can move in any directions (move function). To make things more interesting and close to reality the measurements and the motions are subjected to errors and this is represented by the variables sensor_right and p_move. Given a list of measurements and a list of motions the problem is to create a matrix of probability that describe where the robot is likely to be after all the specified moves.

More information about the definition of the problem can be found on Udacity.

I used the python module unittest for this purpose. This is one of the unit tests that I defined for the problem:

This is the main code that does the actual calculation:

The current algorithm used to solve this problem is called Montecarlo Localization.

You can find the full code in my personal repository.


Tags


You may also like

The best way to stay up to date with C# 10 features

My Technical Journey from my first program to Lead Software Engineer

Top 10 C# Developer News from Microsoft Build 2020

Agile Estimation

{"email":"Email address invalid","url":"Website address invalid","required":"Required field missing"}

Subscribe to our newsletter now!

Get instant access to the Master C# 9 webinar to learn all the new exciting C# 9 features quickly.
Get regular videos and news on C# and .NET and offers on products and services to master C#.

We will collect, use and protect your data in accordance with our Privacy Policy.

>