Particle-Filter-SLAM

Implemented simultaneous localization and mapping (SLAM) using odometry, 2-D LiDAR scans, and stereo camera measurements from an autonomous car. Check the Samples folder for the output.

Details on the underlying technical approach can be found here

Installation

This code uses Python 3.6.

• Install dependencies

$ pip install -r requirements.txt

Data

• Download Sensor amd Stereo Data
• Extract files to data.
• The contents of data should be the following:

param
sensor_data
stereo_images

Note: all python calls below must be run from ./ i.e. home directory of the project

Execution

The following will run the program with default config.

$ python main.py 

If we want the dead reckoning we can run the following command:

$ python main.py --dead-reckoning=True

By default, the dead_reckoning is disabled.

If we want the texture map to be generated at the end we can run the following command:

$ python main.py --texture-map=True

By default, the texture-map is disabled.

We can also set the number of particles, by running the follwing command

$ python main.py --particles=10

By default, the particle filter is initialized with 20 particles.

Maps

Trajectory and the maps can be found in the Samples directory.