This tutorial is a part of the MathWorks Autonomous Construction Vehicle deep dive video series. This tutorial covers how to implement simultaneous localization and mapping (SLAM) for vehicles driving on rough, off-highway terrains. It includes a pre-recorded ROSbag of 3D lidar and motion data from a vehicle driving in a simulated construction site, and a sequence of steps to tune the parameters in the SLAM algorithm provided in Navigation Toolbox for improved results.
Download the entire folder, and run PerformSLAMOnRoughTerrains.mlx
Users are also encouraged to change any parameters in the script to test varations of this demo.
MathWorks Products Required (http://www.mathworks.com)
Requires MATLAB release R2022b or newer. Before proceeding, ensure that the below products are installed:
MATLAB® Navigation Toolbox® ROS Toolbox® Lidar Toolbox®
This demo is created by Dr. Bo Jiang, a MathWorks Engineer as part of the Autonomous Construction Vehicle Webinar(https://www.mathworks.com/videos/design-and-simulating-autonomy-for-construction-vehicles-1679066541903.html)
The license is available in the License file within this repository
Include any other License information here, including third-party content using separate license agreements