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Saved by uncleflo on April 15th, 2012.
I have been asked to explain how the MCL class works. Rather than giving a long written explanation, I've chosen to give a video tutorial. Remember that the source code that I am referring in the video is available for download. Enjoy! Monday, August 23, 2010 Posted by clemency
source carlo monte localization guide tutorial development code lejos mcl
Saved by uncleflo on March 29th, 2012.
Monte Carlo Localization, also known as Particle Filtering, is a relatively new approach to the problem of robot localization - estimating a robot's location in a known environment, given its movements and sensor reading over time. In this project you are to solve the global localization problem, where the robot does not know its starting position but needs to figure out where it is. (This is in contrast to the position tracking problem, where the robot knows its starting position and just need to accommodate the small errors in its odometry that build up over time.) To make things a bit simpler, you will solve this problem in a one dimensional world. Since the on-board computation abilities of the RCX are limited, we remote control the robot from a base computer. You are given skeleton programs for the robot and base computer, which are described below.
monte carlo localization algorithm tutorial guide information science robot university location environment position particle filtering mcl
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