Sensor Fusion Nanodegree | Lidar Obstacle Detection in Autonomous Vehicles
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Updated
Nov 29, 2020 - C++
Sensor Fusion Nanodegree | Lidar Obstacle Detection in Autonomous Vehicles
Tutorial to demonstrate Point Cloud visualization
roshell - An interactive shell for robotics applications
Final project titled "Point Cloud Segmentation and Object Tracking using RGB-D Data" for the Machine Vision (EE 576) course.
In this project we detect, segment and track the obstacles of an ego car and its custom implementation of KDTree, obstacle detection, segmentation, clustering and tracking algorithm in C++ and compare it to the inbuilt algorithm functions of PCL library on a LiDAR's point cloud data.
A QT-based visualization software which can be used to display 3D point clouds from .out and .ply files, which are the outputs of bundler_sfm.
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