LIDAR Obstacle Detection

Description

The goal of this project is to use to various algorithms on Point Cloud data such as Voxel Grid filtering, RANSAC segmentation and Euclidean Clustering with KD-Tree to detect obstacles.

Pipeline

Results

The following animation shows the segmented point clouds - obstacles (in yellow) and road (in green)

Closing thoughts

1. Tracking can used to keep a record of obstacles throughout all the point clouds.
2. 3D Object detection can further aid in determining the type of obstacle (car, traffic signal pole, etc.).