This is the code implementation for the paper UAV Tracking with Solid-State Lidars: Dynamic Multi-Frequency Scan Integration.

This repo contains ROS nodes that implement a relative Monte-Carlo multi-robot localization method by fusing UWB range measurements with odometry estimations and cooperative spatial detections.

This project is used for lidar point cloud undistortion.

Multi-modal multi-lidar dataset

Ultra-wideband (UWB) Localization for Autonomous UAV Flight in GNSS-denied Environments

Basic computer vision pipeline to detect lane lines in a video.

Image processing pipeline for detecting highway lane in a video

CNN and Data Augmentation to train a traffic sign classifier with OpenCv and Tensorflow

CNN model to drive autonomously a car in a simulator using Keras

Vehicle Detection and Tracking pipeline with OpenCV, HOG and SVM.

🏎️ Robot car drivable through hand movements connected to a VR headset

Eye tracking course final project.

A series of image processing algorithms using Three JS and shaders

Image Processing Methods implemented with openMP, CUDA and shared memory

Conversion of 360 stereo images from equirectangular to cube maps using CUDA and OpenMp

Color segmentation via Lab color space using CUDA

Practice exercises using d3.js

LUT trilinear interpolation

Robot arm with 3 degrees of freedom built using three.js

Color Science Lab built using only three.js

Practice exercises using three.js

Extended Kalman Filter and Deep Learning to detect vehicles from RGB and LiDAR data (Sensor Fusion and Tracking project of the Udacity Self-Driving Car Engineer Nanodegree Program)