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Object detection after filtering, segmentation and clustering of point cloud data.

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Obstacle Detection Using LiDAR point cloud data

This project is part of Udacity's Sensor Fusion Course.

In this project we process LiDAR point cloud data using PCL library for object detection. The pipeline includes the follwing steps:

1. Downsampling - Downsample the point cloud to reduce computation.

2. Segmentation - Detect the major plane i.e. road surface using RANSAC.

3. Clustering - Cluster the individual object point clouds together.

4. Bounding Box - Put a bounding box around the individual object point cloud clusters.

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Object detection after filtering, segmentation and clustering of point cloud data.

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