Ray Casting for Implementing Map based Localization in Mobile Robots

The code is an efficient implementation of ray casting used to obtain simulated range measurements.
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Updated 8 Jun 2012

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The code returns simulated range measurements for a robot with a range sensor placed in a known environment. It implements Ray Casting which is an important step for performing Map based localization in Mobile robots using state estimation algorithms such as Extended Kalman Filters, Particle Filters (Sequential Monte Carlo), Markov Localization etc.
The inputs to the castrays.m function are the Robot position, map of environment as logical matrix (Free space = 0, Obstacles = 1), Number of rays to cast, Range of LIDAR in cm.
The function can be used in performing simulations for Mobile robot Localization or for computing importance weights/Measurement probabilities for actual localization.

Cite As

Shikhar Shrestha (2024). Ray Casting for Implementing Map based Localization in Mobile Robots (https://www.mathworks.com/matlabcentral/fileexchange/36892-ray-casting-for-implementing-map-based-localization-in-mobile-robots), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2010a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Ray Casting for Robot Localization/

Version Published Release Notes
1.1.0.0

Corrected a minor error in the code. The upper bound of the for loop has to be n (number of scan lines).

1.0.0.0