jasonsun623,github

lio-mapping

Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)

loam_velodyne

Laser Odometry and Mapping (Loam) is a realtime method for state estimation and mapping using a 3D lidar.

localization-1

The ROS Code doing the localization via laser, publishing the robot pose as well as the position of the poles.

localization_via_wifi_fingerprinting

Multi-Floor Indoor Localization based on Wi-Fi Fingerprinting using various Machine Learning models on the UJIIndoorLoc dataset.

location-1

Smartphone navigation positionning, fusion GPS and IMU sensors.

lol

LOL: Lidar-only Odometry and Localization in 3D point cloud maps

A Planar RGB-D SLAM which utilizes Manhattan World structure to provide optimal camera pose trajectory while also providing a sparse reconstruction containing points, lines and planes, and a dense surfel-based reconstruction.

maoris

Cutting most types of maps in smaller more meaningful bits.

map-based-visual-localization

A general framework for map-based visual localization. It contains 1) Map Generation which support traditional features or deeplearning features. 2) Hierarchical-Localizationvisual in visual(points or line) map. 3)Fusion framework with IMU, wheel odom and GPS sensors.

map_server

map_server for Cartographer

mcl_3dl

A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.