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Transbot SE📖
01.Introduction to Transbot SE
  • 01. Introduction to Transbot SE
  • 02. Precautions for use and battery safety
  • 03. First Trial
02.First Trial
  • 2.1.APP control
  • 2.2.USB wireless handle control(Optional)
  • 2.3.Handle video control Transbot(Optional)
  • 2.4.Network configuration tutorial in hotspot mode
03.Hardware control course
  • 3.1About expansion board and update firmware
  • 3.2.Close self-starting process
  • 3.3.Install Transbot library
  • 3.4.Control buzzer and button
  • 3.5.Control PWM servo
  • 3.6.Control bus servo
  • 3.7.Control motor
  • 3.8.Control robot movement
04.Linux operating system
  • 1. Virtual machine installation and use
  • 2. Linux basics
  • 3. Remote control
  • 4. Multi-machine communication configuration
  • 5. Static IP and hotspot mode
  • 6. Web page real-time monitoring
  • 7. Expansion tutorial
  • 8. Write system images
05.Docker couse(For Pi5)
  • 1.Docker overview and docker installation
  • 2.Common commands for docker image containers
  • 3.Docker images deeply understand and publish images
  • 4.Docker hardware interaction and data processing
  • 5.Start the transbot se container
06.ROS basic course
  • 1.ROS introduction
  • 2.Project file structure
  • 3.Common commands and tools
  • 4.Publisher
  • 5.Subscribers
  • 6.Customize topic messages and use
  • 7.Client
  • 8.Server
  • 9.Custom service messages and usage
  • 10.TF release and monitoring
07.OpenCV courses
  • 1. Getting started with Open Source CV
  • 2. Open Source CV geometric transformation
  • 3. Open Source CV image processing and drawing text line segments
  • 4. Open Source CV image beautification
  • 5. Opencv application
  • 6. AR vision
  • 7. AR QR code
  • 8. ROS+Opencv foundation
  • 9. ROS+Opencv application
  • 10. MediaPipe development
08.ROS robot course
  • 1.PID algorithm
  • 2.Basic communication
  • 3.Keyboard control
  • 4.Handle control(Optional)
  • 5.Robot state estimation
  • 6.Data calibration
09.ROS simple camera course
  • 1.HD camera calibration
  • 2.HD camera color tracking
  • 3.HD camera color tracking (robotic arm)
  • 4.HD camera object tracking
  • 5. KCF target tracking
  • 6.HD camera face tracking
  • 7.HD camera robotic arm carrying
  • 8.HD camera Autopilot
10.ROS robotic arm control tutorial
  • 1.MoveIt configuration
  • 2.MoveIt control the real machine
  • 3.MoveIt moves randomly
  • 4.MoveIt kinematics design
  • 5.MoveIt cartesian path
  • 6.MoveIt avoiding
  • 7.MoveIt scene design
  • 8.MoveIt trajectory planning
  • 9.Mediapipe palm control car
  • 10.Mediapipe gesture control robotic arm
  • 11.Mediapipe gesture control car
  • 12.Mediapipe arm attitude control robotic arm
11.ROS multi-robot control(Optional)
  • 1. Multi-robot control(Optional)
  • 2. Multi-robot queue performance(Optional)
  • 3. Multi-robot robot arm dancing(Optional)
12.Deep learning courses
  • 1.KNN recognizes handwritten digits
  • 2.Basic use of TensorFlow
  • 3.Basic use of PyTorch(jetson)
  • 4.yolov5 model training(jetson)
  • 5.yolov5+tensorrt acceleration(jetson)
  • 6.yolov4-tiny
13.Installation Video
  • Part18
  • Part1-6
  • Part7-12
  • Part13.1-13.3.3
  • Part13.4.1-17
14.FAQnew
  • 1.Using your own Jetson board,Transbot-SE cannot start normally
Download
  • APP(iOS/Android)
  • System_File-Pi5
  • System_File-Pi4
  • System_File-Jetson
  • VM_File
  • Appendix
  • Code
  • InstructionManual
  • Jetson_Boot_USB.tar.gz
  • Hardware_Info
Download ZIP

Welcome to Transbot SE repository

2.HD camera color tracking

HD camera color tracking

2、HD camera color tracking

2、HD camera color tracking2.1、Introduction2.2. Operation steps2.2.1. Start2.2.2. Identification2.2.3. Color calibration2.2.4. Color following

2.1、Introduction

The Transbot SE robot HD camera color tracking is capable of recognizing multiple colors at any time, automatically storing the currently recognized colors.

When controlling the car to follow the detected colors, we need to keep a certain distance from the object.

The color tracking of the Transbot SE robot can also realize the function of real-time HSV regulation. By adjusting the high and low thresholds of HSV, the interfering colors can be filtered out, so that the square can be identified ideally in a complex environment. If the color picking effect is not ideal At this time, we need to move the car to a different environment to calibrate it, so that we can recognize the color we need in a complex environment.

  • HSV

H: 0 — 180

S: 0 — 255

V: 0 — 255

Part of the red is classified as the purple range here:

image-20210908180521035

  • HSV

  • Lightness V

    • Saturation S
  • Hue H

image-20210908180549330

2.2. Operation steps

Note: [R2] on the remote control handle has the [pause/start] function for all gameplays.

2.2.1. Start

jetson motherboard/Raspberry Pi 4B

First start the underlying driver control, which can also be placed in other launch files. (robot side)

roslaunch transbot_bringup bringup.launch

Raspberry Pi 5

Before running, please confirm that the large program has been permanently closed

Enter docker

Note: If there is a terminal that automatically starts docker, or there is a docker terminal that has been opened, you can directly enter the docker terminal to run the command, and there is no need to manually start docker

Start docker manually

xxxxxxxxxx
./run_docker.sh

Start low-level driver control

xxxxxxxxxx
roslaunch transbot_bringup bringup.launch

method one

jetson motherboard/Raspberry Pi 4B

Start the monocular camera (robot side)

xxxxxxxxxx
roslaunch usb_cam usb_cam-test.launch

Start monocular color tracking control (virtual machine)

xxxxxxxxxx
roslaunch transbot_mono mono_tracker.launch VideoSwitch:=false tracker_type:=color

Raspberry Pi 5

Enter the same docker from multiple terminals

Keep the program of the previous docker terminal running and open a new terminal

Enter the following command

xxxxxxxxxx
docker ps

Enter the same docker and use the following 18870bc3dc00 to modify the ID displayed on the actual terminal.

HD camera calibration
HD camera color tracking (robotic arm)

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