MistyMoonR / tsinghua-PX4-ROS

Tsinghua University - Summer vacation project SLAM

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tsinghua-PX4-ROS-README

A lot of things were removed during development, clone this file is recommended depth=1

git clone --depth=1 https://github.com/MistyMoonR/tsinghua-SLAM.git

System environment:

  • Ubuntu18.04.5 LTS x86_64
  • Kernel: 5.4.0-80-generic
  • ROS melodic 1.14.11

Hardware:

  • NUC8 i7-8650U & NUC10 i7-10710U
  • leishen LiDAR C16
  • Camera: RealSense D455 & D435i
  • Xsens Mti-300
  • Routers: AR750S
  • Flight Control: Pixhawk 4
  • A drone

Portal


System framework diagram

IMG

Introduction to the framework

PX4

Representing the UAV PX4 flight control, the sub-projects are Avoidance + Mavros + Realsense

Avoidance is automatic obstacle avoidance for drones
Mavros is the bridge between the PX4 flight control and the ROS environment, via the serial port
Realsense is the working space for the intel depth camera, responsible for ranging, used in conjunction with Avoidance

LIO-SLAM

On behalf of the 3D SLAM modelling project, the sub-projects are lslidar_c16 + mti-300

lslidar_c16 It's a LiDAR ROS workspace
mti-300 It is a 9-axis IMU ROS workspace PS: It was discovered later that the PX4 comes with a nine-axis IMU, this part can be omitted, if you are a beginner, it is advisable to have a high frequency nine-axis IMU, 200Hz or more.


Configuration of the environment requires careful reading of the documentation development


Document description

SLAM Lidar section:

LIO-SAM-dev LIO-SAM ROS open source project environment configuration
LIO-SAM-note LIO-SAM ROS open source project documentation, including LIO-SAM usage on ROS machines, configuration files, problem solutions, etc.

PX4 flight control section:

Autopilot: PX4/Autopliot PX4 ROS open source project , including Mavros and so on, we recommend that newcomers start from the official tutorials
Avoidance-dev: PX4/Avoidance avoidance open source project environment configuration
Avoidance-note: PX4/Avoidance avoidance open source project documentation, including avoidance in ROS machine usage, problem solving and scripting , etc.

data & doc

The documentation for the hardware used in my project is included inside and is organised so that you can see it as you need it. This includes but is not limited to

lslidar_c16
MTi-300
RealSense
rosbag
Spatial
Velodyne_16

scripts

There are two types, one for configuring the ROS environment and one for running ROS programs
Most scripts have the appropriate documentation to require the use of


SLAM Table

SLAM Algorithm with Github Mechanism Appendix & Paper
LIO-SAM CMU Paper: LOAM
LVI-SAM CMU Paper: LVI-SAM
A-LOAM HKUST
FAST-LIO KAIST
LeGO-LOAM Stevens LeGO-Analysis & LeGO-A First Look
SC-LeGO-LOAM KAIST Github: Chinese commentary
XCHU-SLAM Beihang 3D laser SLAM system
LOAM-LIVOX HKU
RPG-SVO-PRO-OPEN UZH

Download the dataset:

Visual Odometry / SLAM Evaluation 2012
jackal_dataset

Data set use:

Github: file_player_mulran
Youtube: How to run MulRan ROS file player

Related papers:

ICRA2021 Paper
ICRA Introduction: https://zhuanlan.zhihu.com/p/388715878


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Tsinghua University - Summer vacation project SLAM


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