There are 52 repositories under sensor-fusion topic.
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
[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.
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 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! đź›°
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]
A highly robust and accurate LiDAR-only, LiDAR-inertial odometry
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)
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.
[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
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.
Kalman filter, sensor fusion
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).
Vehicle State Estimation using Error-State Extended Kalman Filter
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
LIV-Eye: A Low-Cost LiDAR-Inertial-Visual Fusion 3D Sensor for Robotics and Embodied AI.
Modular, open-source implementations of continuous-time simultaneous localization and mapping algorithms.
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
Unscented Kalman Filtering on (Parallelizable) Manifolds (UKF-M)
A simple implementation of some complex Sensor Fusion algorithms
[IROS 2023] Fast LiDAR-Inertial Odometry via Incremental Plane Pre-Fitting and Skeleton Tracking