Starred repositories
OmX - Oh My codeX: Your codex is not alone. Add hooks, agent teams, HUDs, and so much more.
LiDAR Inertial Odometry and Map Matching Localization
Complete Egyptian GNSS positioning suite - Android logger app, MATLAB analysis tools, and satellite positioning algorithms
A computationally efficient and robust LiDAR-inertial odometry (LIO) package
IMU noise characterization using Allan Variance. Extracts noise density and bias instability for SLAM frameworks (GTSAM, LIO-SAM, FAST-LIO).
C++ implementations, derived variants, and compact baselines for localization papers with ROS 2, tests, and benchmarks.
GPU-accelerated GNSS signal processing library (CUDA + Python)
ETL for querying GNSS products needed for PPP
Full Universal Autonomy Stack using Lidar-IMU Odometry
Release repo for our SLAM Handbook
Source code for [TRO2025] VINGS-Mono: Visual Inertial Gaussian Splatting Monocular SLAM in Large Scenes.
A tightly-coupled radar-visual-inertial odometry, to enable robust performance in challenging environments.
Online Estimation of IMU-to-Vehicle Frame Alignment for Ground Vehicles
Source code for the paper "Geometry-Only Urban GNSS Risk Mapping with Phone-Only Data" (Pacific PNT 2026).
A deep network is used to predict the measurement noise covariance and innovation compensation at the satellite level, both of which are directly applied in the EKF update. Meanwhile, dynamic hard …
Factor graph-based loosely-coupled radar-inertial odometry that integrates online temporal calibration.
Dashboard development using AI-ML techniques to interpolate tropospheric Precipitable Water (PW) content using zenith-wet delay from GNSS observations.
Localization using poles and signs detected by LiDAR and GNSS in urban environment
This is the Integrated GNSS Tomography Model (INTOMO) v.`1.0 library. INTOMO is an integrated GNSS tomography tool based on radio occultation and ground-based GNSS observations.
Iterated Error-State Kalman Filter on the SGal(3) Manifold for Fast LiDAR-Inertial Odometry.
Repo for HKUST ELEC5660 Course Notes & Lab Tutorial & Project Docker