Arduino sketches for MPU9250 9DoF with AHRS sensor fusion
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Updated
May 11, 2019 - C++
Arduino sketches for MPU9250 9DoF with AHRS sensor fusion
A Robust, Real-time, RGB-colored, LiDAR-Inertial-Visual tightly-coupled state Estimation and mapping package
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
Implementation of Tightly Coupled 3D Lidar Inertial Odometry and Mapping (LIO-mapping)
Tightly coupled GNSS-Visual-Inertial system for locally smooth and globally consistent state estimation in complex environment.
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
An in-depth step-by-step tutorial for implementing sensor fusion with robot_localization! 🛰
A Fast and Tightly-coupled Sparse-Direct LiDAR-Inertial-Visual Odometry (LIVO).
LiLi-OM is a tightly-coupled, keyframe-based LiDAR-inertial odometry and mapping system for both solid-state-LiDAR and conventional LiDARs.
IMU + X(GNSS, 6DoF Odom) Loosely-Coupled Fusion Localization based on ESKF, IEKF, UKF(UKF/SPKF, JUKF, SVD-UKF) and MAP
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.
TI mmWave radar ROS driver (with sensor fusion and hybrid)
HybVIO visual-inertial odometry and SLAM system
Hoverboard sideboard hack for GD32 boards
ROS package for the Perception (Sensor Processing, Detection, Tracking and Evaluation) of the KITTI Vision Benchmark Suite
Kalman filter, sensor fusion
Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]
Predict dense depth maps from sparse and noisy LiDAR frames guided by RGB images. (Ranked 1st place on KITTI) [2019]
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