lxinghai007

lectures

Material for cuda-mode lectures

r3live

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

IMU-GNSS-Lidar-sensor-fusion-using-Extended-Kalman-Filter-for-State-Estimation

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).

cartographer

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

sync_gps_lidar_imu_cam

lidar-imu-cam-GPS时间戳硬件同步方案

ov-seg

This is the official PyTorch implementation of the paper Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP.

Lidar_AI_Solution

A project demonstrating Lidar related AI solutions, including three GPU accelerated Lidar/camera DL networks (PointPillars, CenterPoint, BEVFusion) and the related libs (cuPCL, 3D SparseConvolution, YUV2RGB, cuOSD,).

openvino_notebooks

📚 Jupyter notebook tutorials for OpenVINO™

Fast-BEV

Fast-BEV: A Fast and Strong Bird’s-Eye View Perception Baseline

designer

Truevision Designer is a 3D tool to design roads, intersections and environments for testing and validating autonomous vehicles and robots.

paper-reading

深度学习经典、新论文逐段精读

ACSC

Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

SensorsCalibration

OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

SegmentAnyRGBD

Segment Any RGBD

TransFusion

[PyTorch] Official implementation of CVPR2022 paper "TransFusion: Robust LiDAR-Camera Fusion for 3D Object Detection with Transformers". https://arxiv.org/abs/2203.11496

BEVFusion

Offical PyTorch implementation of "BEVFusion: A Simple and Robust LiDAR-Camera Fusion Framework"

lidar_IMU_calib

[IROS 2020] Targetless Calibration of LiDAR-IMU System Based on Continuous-time Batch Estimation

imu_gps_localization

Using error-state Kalman filter to fuse the IMU and GPS data for localization.

IMU-Array

IMU array calibration data and navigation test data

HandEyeCalibration

HandEyeCalibration

# 眼在手外相机标定 - Kinect2相机眼在手外标定 aubo机械臂 - CameraIntrinsicCalibration.cpp 内参标定 - CameraIntrinsicCalibration2.cpp 内参标定 - CameraIntrinsicFromFiles.cpp 内参标定写出数据 - HandToEyeCapture.cpp 数据采集保存图片及机械臂关节参数,方便HandToEyeCaptureAuto自动标定 - HandToEyeCalibration.cpp 眼在手外的机械臂外参标定 - HandToEyeCaptureAuto.cpp 眼在手外的机械臂自动标定 - HandToEyeVerify.cpp 眼在手外的标定验证 - HandToEyeVerify2.cpp 眼在手外的标定验证 - astra奥比中光相机眼在手上标定 aubo机械臂 - HandInEyeCapture.cpp 数据采集保存图片及机械臂关节参数,方便HandInEyeCaptureAuto自动标定 - HandInEyeCalibration.cpp 眼在手上的机械臂外参标定 - HandInEyeCaptureAuto.cpp 眼在手上的机械臂自动标定 - HandInEyeVerify.cpp 眼在手上外的标定验证 - HandInEyeVerify2.cpp 眼在手上的标定验证 - 具体眼在手外的机械臂标定操作操作 - 1.先进行图片采集 HandToEyeCapture.cpp - 2.CameraTotrinsicFromFiles.cpp 内参标定写出数据得到内参文件 [眼在外与眼在手上同一个代码标定内参,眼在手外读的是images文件夹,眼在手上读的是images2的文件夹] - 3.HandToEyeCaptureAuto.cpp 眼在手外的机械臂自动外参标定 - 4.HandToEyeVerify2.cpp 眼在手外的标定验证

handeye-calib

基于ROS的手眼标定

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

OpenDRIVE

Unreal Engine OpenDRIVE plugin

BEVFormer

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.

Birds-eye-view-Perception

[IEEE T-PAMI] Awesome BEV perception research and cookbook for all level audience in autonomous diriving

Serial-Studio

Multi-purpose serial data visualization & processing program

Model-Predictive-Control

Udacity Self-Driving Car Engineer Nanodegree. Project: Model Predictive Control

gtsam-examples

GTSAM Tutorial Examples

Dummy-Robot

我的超迷你机械臂机器人项目。