FLVIS: Feedback Loop Based Visual Initial SLAM

Related tags

Deep LearningFLVIS
Overview

FLVIS

Feedback Loop Based Visual Inertial SLAM

1-Video

cla

EuRoC DataSet MH_05 Handheld Test in Lab FlVIS on UAV Platform

2-Relevent Publication:

Under Review, a pre-print version can be found here

3-Support Hardware/Dataset:

Intel RealSense D435i Camera
EuRoC MAV Dataset

4-Build The Project

We have tested in the following environment:
Ubuntu 16.04 + ROS Kinetic
Ubuntu 18.04 + ROS melodic
Clone the repository to the catkin work space eg. /catkin_ws/src

git clone https://github.com/Ttoto/FLVIS.git

Install 3rd Part library

cd catkin_ws/src/FLVIS/3rdPartLib/
./install3rdPartLib.sh

Compile

cd ~/catkin_ws
catkin_make

5-Verification

5.1 D435i Camera Depth Mode

5.1.1 Use our recorded rosbag

Download the dataset Link-melab_sn943222072828.bag to /bag folder
Decompress the rosbag:

rosbag decompress melab_sn943222072828.bag

run the following launch files:

roslaunch flvis rviz.launch
roslaunch flvis flvis_bag.launch
5.1.2 Use your own camera:

Install the realsense driver and its ros wrapper
Boot the d435i camera and echo the camera infomation

roslaunch flvis d435i_depth.launch
rostopic echo /camera/infra1/camera_info

You will get the camera infomation like: As shown, where the resolution is 640x480 and fx=384.16455078125; fy=384.16455078125; cx=320.2144470214844;cy=238.94403076171875.
Edit these information in the config yaml file (say: /launch/d435i/sn943222072828_depth.yaml):

image_width: 640
image_height: 480
cam0_intrinsics: [384.16455078125, 384.16455078125, 320.2144470214844, 238.94403076171875]#fx fy cx cy
cam0_distortion_coeffs: [0.0, 0.0, 0.0, 0.0]#k1 k2 r1 r2

In the launch file "flvis_d435i.launch", make sure "/yamlconfigfile" is point to the edited config file

<param name="/yamlconfigfile" type="string" value="$(find flvis)/launch/d435i/sn943222072828_depth.yaml"/>

run the following launch files:

roslaunch flvis rviz.launch
roslaunch flvis flvis_d435i_depth.launch

5.2 D435i Camera Stero Mode

Like what we did in 5.1.2, we need to config the sn943222072828_stereo.yaml
Note that, by default the two camera share the same intrinsic parameters, and the baseline length is 0.05m:

cam0_intrinsics: [384.16455078125, 384.16455078125, 320.2144470214844, 238.94403076171875]#fx fy cx cy
cam0_distortion_coeffs: [0.0, 0.0, 0.0, 0.0]#k1 k2 r1 r2
cam1_intrinsics: [384.16455078125, 384.16455078125, 320.2144470214844, 238.94403076171875]#fx fy cx cy
cam1_distortion_coeffs: [0.0, 0.0, 0.0, 0.0]#k1 k2 r1 r2
T_cam0_cam1:
[ 1.0,  0.0,  0.0,  0.05,
  0.0,  1.0,  0.0,  0.0,
  0.0,  0.0,  1.0,  0.0,
  0.0,  0.0,  0.0,  1.0]

5.3 EuRoC MAV Dataset

Download the dataset(say MH_05_difficult) into the bag folder:

roscd flvis/bag/
wget http://robotics.ethz.ch/~asl-datasets/ijrr_euroc_mav_dataset/machine_hall/MH_05_difficult/MH_05_difficult.bag

Edit the corresponding bag name in flvis_euroc_mav.launch file:

<node pkg="rosbag" type="play" name="rosbag" args="$(find flvis)/bag/MH_05_difficult.bag"/>

run the following launch files:

roslaunch flvis rviz.launch
roslaunch flvis flvis_euroc_mav.launch

Maintainer:

Shengyang Chen(Dept.ME,PolyU): [email protected]
Yajing Zou(Dept.LSGI,PolyU):[email protected]

Owner
UAV Lab - HKPolyU
The UAV Lab of The Hong Kong Polytechnic University
UAV Lab - HKPolyU
This repository is the offical Pytorch implementation of ContextPose: Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021).

Context Modeling in 3D Human Pose Estimation: A Unified Perspective (CVPR 2021) Introduction This repository is the offical Pytorch implementation of

37 Nov 21, 2022
Implementation of Bagging and AdaBoost Algorithm

Bagging-and-AdaBoost Implementation of Bagging and AdaBoost Algorithm Dataset Red Wine Quality Data Sets For simplicity, we will have 2 classes of win

Zechen Ma 1 Nov 01, 2021
A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes

A Collection of LiDAR-Camera-Calibration Papers, Toolboxes and Notes

443 Jan 06, 2023
Sandbox for training deep learning networks

Deep learning networks This repo is used to research convolutional networks primarily for computer vision tasks. For this purpose, the repo contains (

Oleg Sémery 2.7k Jan 01, 2023
Publication describing 3 ML examples at NSLS-II and interfacing into Bluesky

Machine learning enabling high-throughput and remote operations at large-scale user facilities. Overview This repository contains the source code and

BNL 4 Sep 24, 2022
Experiments with the Robust Binary Interval Search (RBIS) algorithm, a Query-Based prediction algorithm for the Online Search problem.

OnlineSearchRBIS Online Search with Best-Price and Query-Based Predictions This is the implementation of the Robust Binary Interval Search (RBIS) algo

S. K. 1 Apr 16, 2022
Classical OCR DCNN reproduction based on PaddlePaddle framework.

Paddle-SVHN Classical OCR DCNN reproduction based on PaddlePaddle framework. This project reproduces Multi-digit Number Recognition from Street View I

1 Nov 12, 2021
Implementation of Stochastic Image-to-Video Synthesis using cINNs.

Stochastic Image-to-Video Synthesis using cINNs Official PyTorch implementation of Stochastic Image-to-Video Synthesis using cINNs accepted to CVPR202

CompVis Heidelberg 135 Dec 28, 2022
Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image

Inverse Rendering for Complex Indoor Scenes: Shape, Spatially-Varying Lighting and SVBRDF From a Single Image (Project page) Zhengqin Li, Mohammad Sha

209 Jan 05, 2023
Real-world Anomaly Detection in Surveillance Videos- pytorch Re-implementation

Real world Anomaly Detection in Surveillance Videos : Pytorch RE-Implementation This repository is a re-implementation of "Real-world Anomaly Detectio

seominseok 62 Dec 08, 2022
Code for the paper "TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks"

TadGAN: Time Series Anomaly Detection Using Generative Adversarial Networks This is a Python3 / Pytorch implementation of TadGAN paper. The associated

Arun 92 Dec 03, 2022
ALBERT-pytorch-implementation - ALBERT pytorch implementation

ALBERT-pytorch-implementation developing... 모델의 개념이해를 돕기 위한 구현물로 현재 변수명을 상세히 적었고

BG Kim 3 Oct 06, 2022
Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics

14 Nov 06, 2022
Self-Supervised Image Denoising via Iterative Data Refinement

Self-Supervised Image Denoising via Iterative Data Refinement Yi Zhang1, Dasong Li1, Ka Lung Law2, Xiaogang Wang1, Hongwei Qin2, Hongsheng Li1 1CUHK-S

Zhang Yi 72 Jan 01, 2023
A Transformer-Based Feature Segmentation and Region Alignment Method For UAV-View Geo-Localization

University1652-Baseline [Paper] [Slide] [Explore Drone-view Data] [Explore Satellite-view Data] [Explore Street-view Data] [Video Sample] [中文介绍] This

Zhedong Zheng 335 Jan 06, 2023
[ICCV'2021] "SSH: A Self-Supervised Framework for Image Harmonization", Yifan Jiang, He Zhang, Jianming Zhang, Yilin Wang, Zhe Lin, Kalyan Sunkavalli, Simon Chen, Sohrab Amirghodsi, Sarah Kong, Zhangyang Wang

SSH: A Self-Supervised Framework for Image Harmonization (ICCV 2021) code for SSH Representative Examples Main Pipeline RealHM DataSet Google Drive Pr

VITA 86 Dec 02, 2022
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

Donny You 2.2k Jan 06, 2023
BTC-Generator - BTC Generator With Python

Что такое BTC-Generator? Это генератор чеков всеми любимого @BTC_BANKER_BOT Для

DoomGod 3 Aug 24, 2022
Making a music video with Wav2CLIP and VQGAN-CLIP

music2video Overview A repo for making a music video with Wav2CLIP and VQGAN-CLIP. The base code was derived from VQGAN-CLIP The CLIP embedding for au

Joel Jang | 장요엘 163 Dec 26, 2022
Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation

Unseen Object Clustering: Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation Introduction In this work, we propose a new method

NVIDIA Research Projects 132 Dec 13, 2022