This repository allows for fast computation of two-dimensional Time-To-Collision (2D-TTC).

Compute time-to-collision (TTC) using Lidar and Camera sensors. Identify suitable keypoint detector-descriptor combinations for TTC estimation.

🚧 🚔 ⚠ Toolbox to compute Criticality Measures for Automated Vehicles

Project: 2D Feature Tracking || Udacity: Sensor Fusion Engineer Nanodegree

Keypoint Tracking and Matching in Autonomous Vehicles to measure TTC between consecutive frames of the KITTI Dataset

Detect and track objects from the benchmark KITTI dataset. Classify those objects and project them into three dimensions. Fuse those projections together with LiDAR data to create 3D objects to track over time.

A ROS2 project for autonomous car racing RC CAR. Code can run both in the physical car, as well as in simulation.

Tracking the preceding vehicle using Lidar and camera sensors to calculate the Time To Collision (TTC).

Loads images into a ring buffer to optimize memory load and then integrate several keypoint detectors such as HARRIS, FAST, BRISK and SIFT and compares them with regard to number of keypoints and speed.

Udacity ND313 Senor Fusion - Camera Final Project

Time to collision based on lidar and camera data.

Projects Implemented for the Udacity Sensor Fusion Engineer Nanodegree Program