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.

Description

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.

• Required Products: MATLAB
• MATLAB release: MATLAB 7.10 (R2010a)

[Jong Kim]

Hi could you upload your faster model? Thanks

[Shikhar Shrestha]

I have a new optimized version of this code which is much faster and runs almost real-time with a particle set of around 2000 particles. Its can precast on the sample map in 20 minutes at 1 pixel resolution. Do comment if anyone is interested and I will upload the file!