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Muto S2 Robot📖
1.Introduction to Muto Robot
  • 1.Introduction to Muto Robot
  • 2.Accessories introduction
  • 3.Precautions for battery
  • 4.FAQ
2.Assembly and write system
  • 1.Raspberry Pi write system
  • 2.Jetson Nano write sytem
  • 3. Robot assembly tutorial
  • 4. Installation Video Part1-Part5
  • 4. Installation Video Part6-Part10
3.Remote control course
  • 1.Close APP control process
  • 2.Mobile APP remote control tutorial
  • 3.USB wireless handle remote control
4.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.Transfer files remotely
  • 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 sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
5.JupyterLab course
  • 1.ReadMe before operate
  • 2.Environment setup
  • 3.Basic usage tutorial
  • 4.Widgets configuration
  • 5.Widgets controls use
6.Jetson NANO course
  • 1.About JetsonNano system
  • 2.Network configuration and Jtop
  • 3.swap space increased
  • 4.API usage of GPIO library
  • 5.Hardware library configuration
  • 6.Pin reading function
  • 7.Pin level output control
  • 8.Control LED
  • 9.Jetson Nano communicates with external device serial ports
  • 10.jetson nano I2C communication
7.Raspberry Pi course
  • 1.Python usage
  • 2.Use APT to install Python packages
  • 3.Python virtual environment
  • 4.GPIO Zero
  • 5.Pin output high and low levels
  • 6.Pin reads high and low levels
  • 7.Pin output PWM
  • 8.Serial communication
  • 9.I2C communication
8.Robot basic course
  • 1.Control buzzer
  • 2.Control PWM servo
  • 3.Control bus servo
  • 4.Robot forward and backward
  • 5.Robot move left and right
  • 6.Robot rotate left and right
  • 7.Control height
  • 8.Control head
  • 9.Action group performance
  • 10.Read data
  • 11.Host computer control
  • 12.Camera driver
9.Open Source CV course
  • 1.Introduction to Open Source CV
  • 2.Image reading and display
  • 3.Picture writing
  • 4.Image Quality
  • 5.Pixel operations
  • 6.Image zoom
  • 7.Picture cut
  • 8.Picture pan
  • 9.Picture mirroring
  • 10.Affine transformation
  • 11.Picture rotation
  • 12.perspective transformation
  • 13.Grayscale processing
  • 14.Binary image
  • 15.Edge green detection
  • 16.Line segment drawing
  • 17.Rectangular circle drawing
  • 18.Text and picture drawing
7.AI vision course
  • 0.Color HSV value calibration
  • 1.Color recognition
  • 2.Color tracking
  • 3.Color following
  • 4.Color recognition action group
  • 5.Face detection
  • 6.Face tracking
  • 7.Greet people
  • 8.QR code recognition
  • 9.QR code instructions
  • 10.visual line following
  • 11.Motion learning
  • 12.Teach pendant synchronized action
8.Machine deep learning
  • 1.KNN
  • 2.TensorFlow basic tutorial
  • 3.Basic use of PyTorch
  • 4.Yolov5 detects objects in real time
  • 5.Jetson-inference environment construction(selective viewing)
  • 6.Object detection and action
  • 7.Body movement control robot
  • 8.Gesture controlled robot
Remote login control
  • 1. VNC and SSH remote login
  • 2. Jupyter lab login and case code running
9.FAQnew
  • Using your own Jetson board, Muto S2 cannot start normally
Download
  • APP(iOS/Android)
  • SystemFile_For_RPi5
  • System_for_RPi4
  • System_for_JetsonNANO
  • Hardware and protocol
  • Instruction manual
  • Jetson_Boot_USB.tar.gz
Download ZIP

Welcome to Muto S2 Robot repository

8.Gesture controlled robot

8、手势控制机器人

8、Gesture controlled robot

8、Gesture controlled robot8.1、Introduction to gameplay8.2、Core content analysis8.3、Program execution and operation

The Raspberry Pi motherboard series does not currently support this tutorial.

8.1、Introduction to gameplay

The gesture control robot gameplay is a function realized by combining the MediaPipe machine learning framework and the preset action group of the Muto robot. The joint point position information of the fingers is detected through the MediaPipe framework, and how many fingers are first divided according to the characteristics of gestures 1-8. It is in the open state, and then the gestures 1-8 are calculated, which correspond to the eight preset actions for controlling the robot.

8.2、Core content analysis

Initialize the Muto robot and set the initial angle of the camera gimbal. The default is S1=90 and S2=90. The angle of the camera gimbal can be modified according to the actual viewing angle.

self.__robot = Muto()
self.__robot.Gimbal_1_2(90, 90)

Import the mediapipe module and other related modules

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import math
import cv2 as cv
import numpy as np
import mediapipe as mp

Initialize the USB camera. The default is USB camera device /dev/video0. The USB camera device number can be modified according to the device number found in the system.

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capture = cv.VideoCapture(0)
capture.set(6, cv.VideoWriter.fourcc('M', 'J', 'P', 'G'))
capture.set(cv.CAP_PROP_FRAME_WIDTH, 640)
capture.set(cv.CAP_PROP_FRAME_HEIGHT, 480)

Initialize the gesture detection object. detectorCon represents the detection value, which can be modified according to the actual effect. The recommended range is 0.5-1.0.

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hand_detector = handDetector(detectorCon=0.75)

Read the camera image and then transfer it to the findHands function to calculate and output the detection result.

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ret, frame = capture.read()
frame, img = hand_detector.findHands(frame, draw=False)

Determine whether the length of hand_detector.lmList is 0. If it is non-0, it means that the gesture feature is detected. Call the get_gesture function to extract the name of the gesture feature, then display the name on the image, and finally perform related actions.

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if len(hand_detector.lmList) != 0:
    totalFingers = hand_detector.get_gesture()
    cv.rectangle(frame, (0, 430), (230, 480), (0, 255, 0), cv.FILLED)
    cv.putText(frame, str(totalFingers), (10, 470), cv.FONT_HERSHEY_PLAIN, 2, (255, 0, 0), 2)
    # print("Finger", totalFingers)
    hand_detector.parse_action(totalFingers)

The main function of the get_gesture function is to calculate how many of the five fingers are open based on the gesture characteristics. The fingersUp function calculates how many of the five fingers are open, then distinguishes the gesture characteristics based on the angle differences of different gestures, and finally converts them into English characters of the numbers 0-8.

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def get_gesture(self):
        gesture = ""
        fingers = self.fingersUp()
        if fingers.count(1) == 3: gesture = "Three"
        elif fingers.count(1) == 4: gesture = "Four"
        elif fingers.count(1) == 0: gesture = "Zero"
        elif fingers.count(1) == 1: gesture = "One"
        elif fingers.count(1) == 2:
            if fingers[0] == 1 and fingers[4] == 1: gesture = "Six"
            elif fingers[0] == 1 and self.calc_angle(4, 5, 8) > 90: gesture = "Eight"
            else: gesture = "Two"
        elif fingers.count(1)==5:
            if self.get_dist(self.lmList[4][1:], self.lmList[8][1:]) < 60 and \
                    self.get_dist(self.lmList[4][1:], self.lmList[12][1:]) < 60 and \
                    self.get_dist(self.lmList[4][1:], self.lmList[16][1:]) < 60 and \
                    self.get_dist(self.lmList[4][1:], self.lmList[20][1:]) < 60 : gesture = "Seven"
            else:
                gesture = "Five"
        return gesture

Next, the Muto robot is controlled to perform actions according to the name of the gesture feature. If gesture 1 is recognized, action 1 will be performed. If gesture 2 is recognized, action 2 will be performed. And so on. If gesture 8 is recognized, action 8 will be executed.

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def control_robot(self, action):
    if self.count > 0:
        return
    self.count = 20
    if action == "One":
        self.__robot.action(1)
    elif action == "Two":
        self.__robot.action(2)
    elif action == "Three":
        self.__robot.action(3)
    elif action == "Four":
        self.__robot.action(4)
    elif action == "Five":
        self.__robot.action(5)
    elif action == "Six":
        self.__robot.action(6)
    elif action == "Seven":
        self.__robot.action(7)
    elif action == "Eight":
        self.__robot.action(8)
    else:
        self.count = 0
    if self.count > 0:
        print("action:", action)
Body movement control robot
VNC and SSH remote login

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