I have LIDAR data of an environment in my hand and I want to apply likelihood field matching to this data. I found a source. But I don't understand what the variables of the algorithm mean and how it works. Can you help with that?

Note : We're trying to apply the particle filter to a mobile robot. And we will use this algorithm for this.

the algorithm that I found and suggested by my teacher : enter image description here

And the desired result : enter image description here

Thank you for help.

  • $\begingroup$ It's taken from Chapter 6 of Probabilistic Robotics, by Sebastian Thrun, et al, (specifically pp169-174). $\endgroup$ Feb 27, 2019 at 18:26

1 Answer 1


Basically, you are comparing the measurements of your scan with your previously computed map.

You compare all your scans (line 2) for a certain time step that are not range_max (line 3).

You compute the position of your scan based on the position of the robot and the measurements of the scan (lines 4 and 5).

Then, you get the closest occupied cell to your calculated scan position, and compute the distance between the computed scan position and that closest cell (line 6).

Then you get the importance weight based on a normal distribution for that calculated distance (line 7).


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