FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package

A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).

[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving

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

Arduino sketches for MPU9250 9DoF with AHRS sensor fusion

IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP

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

alfred-py: A deep learning utility library for **human**, more detail about the usage of lib to: https://zhuanlan.zhihu.com/p/341446046

X Inertial-aided Visual Odometry

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

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.

An in-depth step-by-step tutorial for implementing sensor fusion with robot_localization! 🛰

LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.

HybVIO visual-inertial odometry and SLAM system

Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [MVA 2019]

Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

Ground-Fusion: A Low-cost Ground SLAM System Robust to Corner Cases (ICRA2024)

[T-RO 24] Swarm-LIO2: Decentralized, Efficient LiDAR-inertial Odometry for UAV Swarms

GLIO: Tightly-Coupled GNSS/LiDAR/IMU Integration for Continuous and Drift-free State Estimation

Modern FOSS Compass and Navigation app without Ads, IAP or Tracking

This is a package for extrinsic calibration between a 3D LiDAR and a camera, described in paper: Improvements to Target-Based 3D LiDAR to Camera Calibration. This package is used for Cassie Blue's 3D LiDAR semantic mapping and automation.

MaRS: A Modular and Robust Sensor-Fusion Framework

LIV-Eye: A Low-Cost LiDAR-Inertial-Visual Fusion 3D Sensor for Robotics and Embodied AI.

A graph-based multi-sensor fusion framework. It can be used to fuse various relative or absolute measurments with IMU readings in real-time.

TI mmWave radar ROS driver (with sensor fusion and hybrid)

Open-source Autonomy Software in Rust-lang using gRPC for the Roomba series robot vacuum cleaners. Under development.

State Estimation and Localization of an autonomous vehicle based on IMU (high rate), GNSS (GPS) and Lidar data with sensor fusion techniques using the Extended Kalman Filter (EKF).

Kalman filter, sensor fusion