A Robust Approach for LiDAR-Inertial Odometry Without Sensor-Specific Modelling

A LiDAR odometry pipeline for wheeled mobile robots

Paper Survey for Deep Visual (-Inertial) Odometry

A highly robust and accurate LiDAR-inertial odometry package

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

Sensor Fusion ROS2 Package enabling dynamic simplified tuning of an Extended Kalman Filter

[NeurIPS 2024] Depth Anything V2. A More Capable Foundation Model for Monocular Depth Estimation

AI-IMU Dead-Reckoning

Minimal, robust, accurate and real-time LiDAR odometry

SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)

Fast and robust global registration for terrestrial robots @ ICRA2022

KISS-ICP: In Defense of Point-to-Point ICP – Simple, Accurate, and Robust Registration If Done in the Right Way https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/vizzo2023ral-iros.pdf

Terraforming Mars board game

Labs for MIT 16.485

Continuous Time LiDAR odometry

LIO-SAM: Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoo…

Multiview Levenberg-Marquardt ICP

LeGO-LOAM: Lightweight and Ground-Optimized Lidar Odometry and Mapping on Variable Terrain

Models and examples built with TensorFlow

This package provides an end-to-end system to laser-based graph SLAM using laser point clouds.

An open autonomous driving platform

A 3D segment based loop-closure algorithm

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

Stanford Code From Cars That Entered DARPA Grand Challenges

Laser Odometry and Mapping (continuous spin version)