An open source platform for visual-inertial navigation research.

An efficient and robust multisensor-aided inertial navigation system with online calibration that is capable of fusing IMU, camera, LiDAR, GPS/GNSS, and wheel sensors. Use cases: VINS/VIO, GPS-INS,…

DALI-SLAM: Degeneracy-Aware LiDAR-inertial SLAM with novel distortion correction and accurate multi-constraint pose graph optimization

DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration

😎 A current list of LiDAR-IMU calibration method

provides nodes for converting the nclt dataset to ROS

Lidar Localization and Mapping

This is a ROS package for lidar odometry implementation using rotation optimization method.

GaRLIO: Gravity enhanced Radar-LiDAR-Inertial Odometry [ICRA 2025]

[IEEE T-RO 2025] iKalibr: Multi-Sensor Calibration (Extrinsics & Time Offsets)

C++ implementation of Lie Groups using Eigen.

A highly robust and accurate LiDAR-only, LiDAR-inertial odometry

Additional descriptions about the Pohang Canal Dataset

RIO - EKF-based Radar Inertial Odometry using 4D mmWave radar sensors

REVE - Radar Ego Velocity Estimator: Robust 3D ego velocity estimation using 4D mmWave radar sensors.

This repository shares the documentation and development kit of the View of Delft automotive dataset.

(T-IV) Radar4Motion: 4D Imaging Radar based IMU-free Odometry with Radar Cross Section (RCS) weighted Correspondences

Python package for the evaluation of odometry and SLAM

RIO - EKF-based Radar Inertial Odometry using 4D mmWave radar sensors

High precision time synchronization for the Teensy 4.1 microcontroller platform

MSF - Modular framework for multi sensor fusion based on an Extended Kalman Filter (EKF)

LiDAR degeneracy dataset for LiDAR-radar-inertial fusion methods.

Integrates an IMU to predict future odometry readings

Cross-platform, Serial Port library written in C++

A ROS client library for small, embedded devices, such as Arduino. See: http://wiki.ros.org/rosserial

This package implements a simple tree detector from point cloud data. It makes no assumptions about the ground plane and can handle arbitrary terrains.

This package provides localization in a pre-built map using ICP and odometry (or the IMU measurements).

The tight integration of FAST-LIO with Radius-Search-based loop closure module. Forked from