08. Lidar Obstacle Detection Project
Header Text
Lidar Obstacle Detection Project
ND313 C1 L4 A30 Lidar Obstacle Detection Project [LB]
Project Details
In this project you will take everything that you have learned for processing point clouds, and use it to detect car and trucks on a narrow street using lidar. The detection pipeline should follow the covered methods, filtering, segmentation, clustering, and bounding boxes. Also the segmentation, and clustering methods should be created from scratch using the previous lesson’s guidelines for reference. The finished result will look like the image below, placing bounding boxes around all obstacles on the road.
Project Results
Lidar Obstacle Detection.
Workspace
This section contains either a workspace (it can be a Jupyter Notebook workspace or an online code editor work space, etc.) and it cannot be automatically downloaded to be generated here. Please access the classroom with your account and manually download the workspace to your local machine. Note that for some courses, Udacity upload the workspace files onto https://github.com/udacity , so you may be able to download them there.
Workspace Information:
- Default file path:
- Workspace type: react
- Opened files (when workspace is loaded): n/a