Cartographer is a system that provides real-time simultaneous localization and mapping (SLAM) in 2D and 3D across multiple platforms and sensor configurations.

RTAB-Map library and standalone application

cpp implementation of robotics algorithms including localization, mapping, SLAM, path planning and control

Visual Inertial Odometry with SLAM capabilities and 3D Mesh generation.

Real-time 3D localization using a (velodyne) 3D LIDAR

Fast LOAM: Fast and Optimized Lidar Odometry And Mapping for indoor/outdoor localization IROS 2021

Tightly coupled GNSS-Visual-Inertial system for locally smooth and globally consistent state estimation in complex environment.

[IEEE RA-L & ICRA'22] A lightweight and computationally-efficient frontend LiDAR odometry solution with consistent and accurate localization.

Point cloud registration pipeline for robot localization and 3D perception

[IEEE ICRA'23] A new lightweight LiDAR-inertial odometry algorithm with a novel coarse-to-fine approach in constructing continuous-time trajectories for precise motion correction.

A simple localization framework that can re-localize in built maps based on FAST-LIO.

Robocentric Visual-Inertial Odometry

GLIM: versatile and extensible point cloud-based 3D localization and mapping framework

Visual SLAM/odometry package based on NVIDIA-accelerated cuVSLAM

Precise localization based on GNSS and IMU.

A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.

ROS 2 package of 3D lidar slam using ndt/gicp registration and pose-optimization

Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion. ICCA 2018

OV²SLAM is a Fully Online and Versatile Visual SLAM for Real-Time Applications

Intensity Scan Context based full SLAM implementation for autonomous driving. ICRA 2020