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An implementation of particle filtering algorithm for simultaneous localization and mapping (SLAM) in autonomous robots.

Simultaneous Localization and Mapping through Particle Filtering

An implementation of particle filtering algorithm for Simultaneous Localization and Mapping (SLAM)

Update: This was my assignment from grad school in 2007, I have not attempted to run it since and neither should you be attempting to run this code. I uploaded this to GitHub as it brough back pleasant old memories.

Usage

python slam.py <datafile [ex:data/localized.data]> <cell size [ex:20]> <Type (-1/0/1/2,3) [ex:0]>"

Demo

Here's a movie demonstrating SLAM in action on the file data/localized.data. This is a simulation of the robot receiving real-time data from its LASER range finder and SONAR and using SLAM to build a map of its surrounding and positioning itself in that environment.

SLAM in Action