/SFND_Lidar_Obstacle_Detection

This is the project submission for the "Lidar Obstacle Detection Project" in the Udacity Sensor Fusion Engineer Nanodegree program.

Primary LanguageMakefile

Project Submission

Here, you can find the project submission for Sensor Fusion Self-Driving Course "Lidar Obstacle Detection Project". In this example, RANSAC, 3D KD-Tree, and Euclidean clustering algorithms are customly modelled according to project rubric. The requirements to be successful in the project are listed below:

  • Bounding boxes enclose appropriate objects.
  • Objects are consistently detected across frames in the video.
  • Segmentation is implemented in the project.
  • Clustering is implemented in the project.

You can see the screen recording from the project result:

Udacity Link for Sensor Fusion Course