Name: Vezeteu Eugeniu
Type: User
Company: Finnish Geospatial Research Insitute, Aalto University
Bio: Computer vision | Sensor fusion, Autonomous driving | Robot Navigation | Perception and Localization | LiDAR and Camera mapping.
Location: Helsinki, Finland
Blog: https://eugeniu1994.github.io/EugeniuVezeteu.github.io/
Vezeteu Eugeniu's Projects
Keyframe based pose-graph 3D slam
Autonomous driving car Udacity simulator - User behaviour cloning
Autonomous driving agent, Behavioural cloning
Mirror of the Basalt-Headers repository. All pull requests and issues should be sent to https://gitlab.com/VladyslavUsenko/basalt-headers
Simple 2D point-to-point scan matcher implemented in Python. Works with ROS1.
Camera calibration based on OpenCV. Data points are collected either with Chessboard, ArUco or ChArUco target.
Computer Vision course at Aalto University.
https://eugeniu1994.github.io/EugeniuVezeteu.github.io/
the public implementation of "FRIS-LOAM: Fast Range Image Segmentation for LiDAR Odometry and Mapping in complex environments" paper
Developed state of art to localize vehicle using GPS, LIDAR and IMU sensors
State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).
Tutorial for using Kitti dataset easily
The code implemented in ROS projects a point cloud obtained by a Velodyne VLP16 3D-Lidar sensor on an image from an RGB camera.
LOAM algorithm to use with the KITTI Dataset
Machine Learning lab course at the Technical University of Berlin. Covers supervised and unsupervised learning techniques.
NTD - slam front-end
Performance comparison of NearestSearch and radiusSearch function in point cloud.
Computation of coherently aligned pointcloud normals using nanoflann for neighbour search and Eigen for eigenvector computation.
Reinforcement learning final project at Aalto University, Policy gradient agent learn to play pong game from image data.
This is an example of indoor RGB-D SLAM
Robotics and AI final project course at the Technical University of Berlin. Pong game played by panda robots.
S-PTAM: Stereo Parallel Tracking and Mapping, python implementation
Coursera Open Courses from University of Toronto
Sensor fusion final project at Aalto University. IMU calibration, Extended Kalman Filter, Particle Filter.
Sensor fusion course at Aalto University.
Applied Artificial Intelligence project course at the Technical University of Berlin. Small scale autonomous driving. Covers basic perception and control algorithm.