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MicroROS Robot📖
01. Introduction
  • 0.Unpacking and reviewing video
  • 1. ReadMe - learning route
  • 2. Introduction to lidar
  • 3. Introduction to microROS control board
  • 4. FAQ
  • 5. About charging
02. Assembly course
  • Assembly steps
03. Preparation
  • First Trial
  • 1. Write firmware
  • 2. How to install and use VM
  • 3. microROS control board configuration
  • 4. Connect to microROS agent
04. VM Remote control course
  • 1. VM keyboard remote control
  • 2. VM handle remote control
05.ROS-WiFi module configuration
  • 0. Serial port configuration WiFi instructions
  • 1.Module usage in car(ReadMe)
  • 2.Connection module proxy
  • 3.Camera picture correction(ReadMe)
  • 4.Calibrate servo PTZ(ReadMe)
06.ROS+OpenCV course
  • 1.OpenCV Getting started
  • 2.Geometric transformation
  • 3.Image processing and drawing text line segments
  • 4.Image beautification
07.Mediapipe course
  • 1. Hand detection
  • 2. Posture detection
  • 3. Overall inspection
  • 4. Face detection
  • 5. Face recognition
  • 6. Facial effects
  • 7. 3D object recognition
  • 8. Brush
  • 9. Finger control
  • 10. Gesture recognition
08. Robot basic course
  • 1. Robot information release
  • 2. Robot keyboard control
  • 3. Robot handle control
  • 4. Robot state estimation
  • 5. Linear speed calibration
  • 6. Angular velocity calibration
  • 7. Robot URDF model
09. Lidar course
  • 1. Lidar avoid
  • 2. Lidar following
  • 3. Lidar guard
  • 4. Lidarpatrol
  • 5. Gmapping mapping
  • 6. Cartographer mapping
  • 7. Navigation2 navigation avoid
  • 8. ROS Robot APP mapping
  • 9. ROS Robot APP navigation
10. Multi-machine course
  • 1. Multi-machine handle control
  • 2.Multi-machine keyboard control
  • 3. Multi-machine navigation
11.Robot visual interaction
  • 1. Color tracking
  • 2. Object recognition and tracking
  • 3.Face recognition tracking
  • 4.Autonomous driving line patrol
  • 5.QR code motion control
  • 6.Gesture control car movement
  • 7.Palm control car movement
  • 8.Gesture control car action group
  • 9.Palm control 2DOF servo PTZ
12. Linux basic course
  • 1. Introduction to Linux system
  • 2. Ubuntu file system
  • 3. Ubuntu common commands
  • 4. Ubuntu common editors
  • 5. Ubuntu software operation commands
  • 6. Virtual machine installation
  • 7. SSH remote control
  • 8. VNC remote control
  • 9. Remote file transfer
  • 10. Driver library and communication
  • 11. Static IP and hotspot mode
  • 12. Bind device ID
  • 13. Capacity expansion and resource allocation
  • 14. Update system software source
  • 15. set root password
  • 16. sudo free password
  • 17. Connect to WiFi network
  • 18. View system version
  • 19. Customized service management
  • 20. Back up system image
13. Docker course
  • 1. Overview and installation
  • 2. Common commands
  • 3. In-depth understand and publishing images
  • 4. Hardware interaction and data processing
  • 5. Enter robot docker container
18.ROS2 basic course
  • 1. Introduction to ROS2
  • 2.ROS2 install Humble
  • 3. ROS2 development environment
  • 4. ROS2 workspace
  • 5. ROS2 function package
  • 6. ROS2 node
  • 7.ROS2 topic communication
  • 8. ROS2 service communication
  • 9. ROS2 action communication
  • 10. ROS2 custom interface message
  • 11. ROS2 parameter service case
  • 12. ROS2 meta-function package
  • 13. ROS2 distributed communication
  • 14. ROS2 DDS
  • 15. ROS2 time related API
  • 16. ROS2 common command tools
  • 17. ROS2 rviz2 use
  • 18. ROS2 rqt toolbox
  • 19. ROS2 Launch startup file configuration
  • 20. ROS2 recording and playback tool
  • 21. ROS2 URDF model
  • 22. ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
15. microROS control board development environment
  • 1. Introduction to microROS control board
  • 2. Set up ESP32-IDF development environment
  • 3. ESP32-IDF configuration tool
  • 4. Install ESP32-microros components
  • 5. Install and start microROS agent
  • 6. Flash-tool burning firmware
16. ESP32 basic course
  • 1. Turn on the LED light
  • 2. Button function
  • 3. Drive the buzzer
  • 4. Serial communication
  • 5. Battery voltage detection
  • 6. Drive PWM servo
  • 7. Drive motor
  • 8. Read motor encoder data
  • 9. PID controls car speed
  • 10. Read IMU data
  • 11. Read radar data
  • 12. Flash access data
  • 13. Partition table and memory
  • 14. Bluetooth communication
  • 15. WiFi networking
  • 16. Robot kinematics analysis
  • 17. ROS-WiFi camera module
17. microros basic course
  • 1. Publish topic
  • 2. Subscribe topic
  • 3. Multi-topic subscribe and publish
  • 4. Subscribe buzzer topics
  • 5. Subscribe PWM servo topics
  • 6. Subscribe speed control topics
  • 7. Release speed topic
  • 8. Release IMU data topic
  • 9. Publish lidar data topics
  • 10. Customized transmission method
Download
  • Mapping_APP(iOS_Android)
  • Code and firmware
  • Hardware info and driver software
  • VM image file
  • Instruction manual
  • SystemFile_RPi
  • SystemFile_JetsonNANO
  • 3D_Model_File
  • ROS2_Basic_VM
Download ZIP

Welcome to MicroROS Robot repository

3. Lidar guard

Lidar guard

Note: The virtual machine needs to be in the same LAN as the car, and the ROS_DOMAIN_ID needs to be consistent. You can check [Must read before use] to set the IP and ROS_DOMAIN_ID on the board.

1. Program function description

The car connects to the agent and runs the program. The radar on the car scans the nearest object within the set range and tracks the object through rotation. If the object is closer to the radar than the set distance, the buzzer on the car will Sounds as a warning. Parameters such as the radar detection range and obstacle avoidance detection distance can be adjusted through the dynamic parameter adjuster.

2. Start and connect to the agent

Taking the supporting virtual machine as an example, enter the following command to start the agent:

sudo docker run -it --rm -v /dev:/dev -v /dev/shm:/dev/shm --privileged --net=host microros/micro-ros-agent:humble udp4 --port 8090 -v4

image-20240102120220511

Then, turn on the car switch and wait for the car to connect to the agent. The connection is successful, as shown in the figure below.

image-20231218154638683

3. Start the program

Enter the following command in the terminal to start:

xxxxxxxxxx
ros2 run yahboomcar_laser laser_Warning

image-20231218154818575

After the program is started, it will search for the nearest object within the radar scanning range, move the object slowly, and the car will follow the object through rotation.

As shown in the picture above, if the set range is not exceeded, [no obstacles@] will be printed. If an obstacle appears, [---------------] will be printed and the buzzer will sound. Some parameters can be set through the dynamic parameter adjuster and terminal input.

xxxxxxxxxx
ros2 run rqt_reconfigure rqt_reconfigure

image-20231218155628200

Note: There may not be the above nodes when you first open it. You can see all nodes after clicking Refresh. The displayed laser_Warning is the node of the radar guard.

Description of the above parameters:

  • LaserAngle:Radar detection angle

  • ResponseDist:tracking distance

  • Switch:Game switch

After modifying the above parameters, you need to click on the blank space to transfer the parameters into the program.

4. Code analysis

Source code reference path (taking the supporting virtual machine as an example):

xxxxxxxxxx
/home/yahboom/yahboomcar_ws/src/yahboomcar_laser/yahboomcar_laser

laser_Warning.py, the core code is as follows,

x
#Create a radar subscriber to subscribe to radar data and remote control data and a speed publisher to publish speed data and a buzzer publisher to publish buzzer control data.
self.sub_laser = self.create_subscription(LaserScan,"/scan",self.registerScan,1)
self.sub_JoyState = self.create_subscription(Bool,'/JoyState',
self.JoyStateCallback,1)
self.pub_vel = self.create_publisher(Twist,'/cmd_vel',1)
self.pub_Buzzer = self.create_publisher(UInt16,'/beep',1)
#Radar callback function: processes subscribed radar data
ranges = np.array(scan_data.ranges)
minDistList = []
minDistIDList = []
for i in range(len(ranges)):
    angle = (scan_data.angle_min + scan_data.angle_increment * i) * RAD2DEG
#Find the nearest object within the radar detection range according to the set radar detection angle
if angle > 180: angle = angle - 360
if  abs(angle) < self.LaserAngle and ranges[i] > 0:
    minDistList.append(ranges[i])
    minDistIDList.append(angle)
if len(minDistList) != 0: 
    minDist = min(minDistList)
    minDistID = minDistIDList[minDistList.index(minDist)]
else:
    return
#Based on the position deviation from the tracking object, the angular velocity is calculated so that the front of the car is aligned with the object.
angle_pid_compute = self.ang_pid.pid_compute(minDistID/48, 0)
if abs(angle_pid_compute) < 0.1:
    velocity.angular.z = 0.0
else:
    velocity.angular.z = angle_pid_compute
self.pub_vel.publish(velocity)
#Determine whether the radar detection distance of the smallest object is less than the set range, and then make a judgment whether the buzzer needs to sound.
if minDist <= self.ResponseDist:
    print("---------------")
    b = UInt16()
    b.data = 1
    self.pub_Buzzer.publish(b)

else:
    print("no obstacles@")
    b = UInt16()
    b.data = 0
    self.pub_Buzzer.publish(UInt16())

 

Lidar following
Lidarpatrol

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