Author Archive:amber

Byamber

Raspberry Pi Robot Car DIY Learning Kit Lesson 1: Basic Framework Installation

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Objective

In this lesson, we will install the most important framework in the smart car and make car to do some simple movements as per our python sample code. If you have passed the test movement of this lesson, that means Arduino, voltage meter,motor drive module(Model-PI), motors, batteries,chassis and wire connections between these parts are all functioning well.
As your experiments in future lessons are all based on frame work of Lesson One, it is very important to test the installation and sample code in this Lesson properly.

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Hardware Installation

Video intutorial for SD Card Pre-installed OSOYOO Image

Video intutorial for Your SD Card

STEP1. Install driving wheels as follows.

STEP2. Install universal wheel as follows.

STEP3. Install PCA9685 compatible module.

STEP4. Install voltage meter as follows.

STEP5. Install 5 pcs tracking sensor as follows.

STEP6.Plug the 4 pin female to female cable (white,red,black,yellow) and 2 pin female to female cable(black,red) into PCA9685 compatible board as follows.

STEP7.Plug the 2 PCS 1 pin to 5 pin female to female cable (Black and Red) into PCA9685 compatible board as follows.

STEP8.Install the model pi motor driver board as follows. Then connect PCA9685 compatible module to motor driver board via 4pin and 2 pin cable.Meanwhile, connect the voltage meter to motor driver board via 3pin cable.

STEP9.Install camera module on the top car chassis as follows.

STEP10.Install battery box on the top car chassis as follows.

STEP11.Install raspberry pi on the top car chassis as follows.

STEP12.Intall the top chassis as follows.

STEP13.Before intall the top chassis as follows, you need to plug the battery box into model pi motor driver, then connect the Raspberry Pi board to PCA9685 compatible module adn model Pi motor driver board as follows.

STEP14.Install the left and right wheels.

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Software Installation

Software Preparation:Imager utility: Win32DiskImager utility

OS: Raspbian (Use OS Raspbian 2018-04-18 in the subsequent tutorials)

Format Tool: SDFormatter (Optional)

SSH Tool: PuTTY (for Windows users)

Step 0:Before connect to Raspberry Pi, you need to install Raspbian Operation System(OS) onto SD card(skip this step if your SD card has pre-installed Osoyoo Robot Image).You can select the latest version of RASPBIAN system on the official website: https://downloads.raspberrypi.org/raspbian/images/. Write the image via Win32DiskImager utility into your microSD/TF card(minimum 16G), then plug the card into the slot on your Raspberry Pi.Step 1: Connect Wifi
Firstly, Connect Raspberry Pi to your HDMI monitor or TV. Put a keyboard and mouse into Raspberry Pi USB ports. Insert SD card into the slot on your Raspberry Pi.Click on the wireless icon top right on desktop, should give a list of access points, select your wifi ssid and connect it. Once your Pi is connect to Wifi, you can hover your mouse to the wifi icon to see the your IP address.

Or your can type sudo ifconfig wlan0 command in terminal. Your local ip address will show in wlan0 block(right side of the word inet addr:). It will look like 192.168……

Please remember above IP address, it will be used in our next steps.

Important Note:As the raspberry pi robot car image was written into SD Card, you just need to follow the step 1 to connect wifi and skip Step 2 to Step 5, directly run the Testing Python code.

Step 2: Open SSH connection

SSH enable user to type shell command remotely from internet so that we can control the car through wifi.In order to enable SSH function, we need type following command from terminal:

sudo raspi-config

Then select Interfacing Options->SSH->Yes->Ok->Finish

Step 3:Use SSH to connect Raspberry Pi terminal remotely

In order to make the car moving freely, we need disconnect Raspberry Pi from monitor, keyboard/mouse and use SSH to send command to Raspberry Pi terminal remotely.

If you are using Windows to send ssh command. you need download a free software called PuTTy to connect the Raspberry Pi local IP(you got from STEP 1).

If you are using MacBook or other linux computer, please type: ssh pi@192.168.50.7

ssh your_raspberry_pi_local_ip_address

*your_raspberry_pi_local_ip_address means the wifi IP address you got from STEP 1

When connecting ssh, you need use default user name pi and default password raspberry to login to Raspberry Pi.

Step 4: Open I2C function(skip this step if your SD card has pre-installed Osoyoo Robot Image)

I2C is a protocol which will be used to exchange data with I2C device. In our project, I2C device is PCA9685 module.In order to use I2C function, we need type following command from terminal:

sudo raspi-config

Then select Interfacing Options->I2C->Yes->Ok->Finish


Step 5: Install GPIO Library(skip this step if your SD card has pre-installed Osoyoo Robot Image)

  • Update Rasbian Repository by typing following terminal command
cd ~ 
sudo apt-get update
  • Install python-pip , python-sumbus and github
sudo apt-get install build-essential python-pip python-dev python-smbus git
  • Install GPIO Library by typing following terminal command
git clone https://github.com/adafruit/Adafruit_Python_GPIO.git 
cd Adafruit_Python_GPIO 
sudo python setup.py install
  • Typing following terminal command to remove installation files and save disk space
cd ~ 
sudo rm -fr Adafruit_Python_GPIO

Step 5:Testing Previous Installation(skip this step if your SD card has pre-installed Osoyoo Robot Image)

  • Download testing python code by typing following commands:
cd ~ 
mkdir osoyoo-robot/ 
cd osoyoo-robot/ 
wget http://osoyoo.com/driver/motor-test.tar.gz
tar -zxvf motor-test.tar.gz

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Testing

Step 6: Run Testing Python code

cd ~/osoyoo-robot/motor-test
python motor-test.py

Important Note:As the raspberry pi robot car image was written into SD Card, you just need to follow the step 1 to connect wifi and skip others steps, directly run the Testing Python code.

After running above python sample code, your car should move forward for 2 seconds, then move backward for 2 seconds , then turn left for 2 seconds and finally turn right for 2 seconds.

If your car does not move as per above scenario, the installation should have some problem. You need double check the wire connection and software installation as per our previous steps.

Byamber

Raspberry Pi Robot Car DIY Learning Kit Lesson 2: Line Follow

 

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Objective

In this lesson, we will use black/white tracking sensors to guide robot car to trace a black track in the white ground. If you have not completed installation in Lesson 1, please review Lesson 1.

(Note: in lesson 1, 5 black/white tracking sensors have been installed and connected to Raspberry Pi to prepare for lesson 2)

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Hardware Installation

If you don’t install 5 tracking sensor modules in lesson1, please install and connect these modules as following pictures. If you have already installed and connected these, please skip this step.


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Software Installation

Note:
1. if you use our image as OS system as lesson1, please skip Software Installation and go to Step2 to adjust the sensitivity of tracking sensor module or the step “test tracking line”
2. Please keep the raspberry Pi on power when using SSH to send command to Raspberry Pi terminal remotely.

Step 1:Download line-tracking sample code with following terminal command(skip this step if your micro SD card has pre-installed Osoyoo Robot Image):
cd ~/osoyoo-robot/
wget http://osoyoo.com/driver/lf.tar.gz
tar -zxvf lf.tar.gz

Note: Above commands will download sample code file to osoyoo-robot/lf directory

Step 2: Test Black/White Tracking sensors

There are 5 black/white tracking sensors in the forehead of the car. Each sensor has two LED lights . The red LED indicates power. The green LED indicates black/white. When black is detected, Green LED will turn off and a “1” will be sent to Raspberry Pi GPIO pin, otherwise LED will ON and a “0” will be sent.
* To make sensors working properly, you need use a screw driver to adjust the sensitivity screw on each sensor and make sure Green LED will ON when it is over White and Off when it is over Black.

If you want to learn more about adjust tracking module, please follow the next vedio:

Following python code and experiment will tell you if the sensors are installed correctly.
First, put a 2 cm black track on white ground, then put your car over the track and turn on battery.
Next, use SSH to connect your Raspberry Pi remotely from your PC(use Putty if you are using Windows), and type following terminal command:

cd ~/osoyoo-robot/lf
python test.py

When your put the first sensor(from right) on the black track, the green LED will turn off and your will see Putty terminal window show 00001 as following:

This means Raspberry Pi detected WHITE(0) from 4 sensors in the left and Black(1) from the right edge sensor. You can change the position of the black track from right to left sensors one by one and make the result change from 00001 to 00010,00100,01000,10000.If your result is not showed as above, you might need to double check if the sensor sensitivity and connection to the Pi is correct.

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Testing line tracking

First, make a black track on white ground. The track can be round or curve , but the turning angle of each curve should not be too sharp. We suggest user use 2cm width black tape sticking on white ceramic tile and make a nice track.

Next put your car over the track and turn on the power switch on battery box.

Last, use SSH to connect Raspberry Pi through your PC and typing following commands:
cd ~/osoyoo-robot/lf
python line_follow.py

After above command is sent to raspberry Pi, your car will start moving along the black track automatically.

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Byamber

Raspberry Pi Robot Car DIY Learning Kit Lesson 3: Web Control Camera

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Objective

In this lesson, we will learn how to let the robot car has vision to see front environment and how to control the robot car through web browser or mobile APP.

To complete this task, we need install a web server software called “mjpg-streamer” in Raspberry Pi, this software will catch video from Robot Car camera and send the video to a web page.

We also need to install another web server software called “WebIOPi” in Raspberry Pi. This software will allow user to use browser to remotely control Raspberry Pi GPIO input/output and therefore control the movement of our robot motor.

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Hardware Installation

If you don’t install camera in lesson1, please install and connect camera as following pictures. If you have already installed and connected these, please skip this step.


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Software Installation

Note:
1. If your micro SD card has pre-installed Osoyoo Robot Image,please skip Step 1 to Step 8 and direct Run Step 9: Testing
2. Please keep the Raspberry Pi on battery power when using SSH to send command to Raspberry Pi terminal remotely.

Step 1: Download WebIOPi/mjpg-streamer installation package by running following terminal commands(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

cd ~
sudo apt-get install rpi.gpio -y
mkdir osoyoo-robot/cam-robot
cd osoyoo-robot/cam-robot
wget http://osoyoo.com/driver/WebIOPi-0.7.1.tar.gz
wget http://osoyoo.com/driver/mjpg-streamer.tar.gz
wget http://osoyoo.com/driver/robot.tar.gz
tar -xzvf WebIOPi-0.7.1.tar.gz
tar -xzvf mjpg-streamer.tar.gz
tar -xzvf robot.tar.gz

Following Step 2 to 4 are for WebIOPI server Installation

Step 2: Download and install WebIOPi patch by running following terminal command(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

cd ~/osoyoo-robot/cam-robot/WebIOPi-0.7.1/
wget http://osoyoo.com/driver/webiopi-pi2bplus.patch
patch -p1 -i webiopi-pi2bplus.patch

Step 3: Install WebIOPi by running following terminal command(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)
sudo ./setup.sh

You need verify the installation by typing following command
webiopi -h

If WebIOPi is installed successfully, you will see following message in terminal, otherwise you might need redo the download and installation.

Step 4: Run webiopi by typing following command:(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

sudo webiopi -d -c /etc/webiopi/config

Use a browser in another computer (your computer/PAD/Phone in same LAN of your Pi) to visit your Pi’s IP address with port “8000” ( i.e http://192.168.0.115:8000, please replace 192.168.0.115 with your Pi’s local IP address), your browser will show WebIOPi login page. You need use default WebIOPi user name “webiopi” and default password “raspberry” to login to the server. Once you are logged into WebIOPi page, you will see WebIOPI Main Menu as following. If you can not see this page , you need to reinstall the WebIOPI software.

Please press “Ctrl” + “C” then “Ctrl” + “Z” in your terminal to end WebIOPi running.

Note: If you don’t know your raspberry pi IP address, type following command in your terminal,
ifconfig wlan0

Your raspberry Pi IP address is in the right side of the word inet addr:

Following Step 5 to 7 is for mjpg-streamer server Installation

Step 5: If you are using CSI camera , please take following action as per step A and B. (If you are using USB camera which comes with the car, please skip this step)(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

A. enable camera in Raspberry Pi
sudo raspi-config

B. edit “/etc/modules” file by typing following command(otherwise /dev has no camera device node)
sudo nano /etc/modules

Please add the following line in the bottom of the “/etc/modules” file, and then press “ctrl” + “x” and then “y” to save the file and press “enter” exist nano editor
bcm2835-v4l2

Step 6: download and install mjpg-streamer support library by typing following command(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

cd ~
sudo apt-get update
sudo apt-get install libv4l-dev libjpeg8-dev -y
sudo apt-get install subversion -y

Step 7: Compile mjpg-streamer(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

Firstly, edit the configuration file “input_uvc.c” by typing following command
cd ~/osoyoo-robot/cam-robot/mjpg-streamer/plugins/input_uvc
sudo nano input_uvc.c

Find following line(you can use “ctrl” + “W” to search the line when you enter nano editor)

 int width=640, height=480, fps=5, format=V4L2_PIX_FMT_MJPEG

Replace the string V4L2_PIX_FMT_MJPEG with new string V4L2_PIX_FMT_YUYV

Then press “ctrl” + “x” and then “y” to save the file and press “enter” exist nano editor

Secondly, we need compile the source code with following commands:
cd ~/osoyoo-robot/cam-robot/mjpg-streamer
make all

Thirdly, test camera installation: Plug your camera into Raspberry Pi, then type following command:
ls /dev/video*

You should see following result in your terminal, “/dev/video0” is the camera installed in Pi

At last, Run mjpg-streamer Server by typing following command in terminal:
cd ~/osoyoo-robot/cam-robot/mjpg-streamer
sudo ./start.sh

Now use browser in another computer to access your Raspberry Pi IP address with port 8899 (i.e, if your Pi IP address is 192.168.0.115, visit http://192.168.0.115:8899 in your browser), you will see following image. Click Stream button in left menu, you will see the real time video captched by the camera in your Raspberry Pi

You can use Ctrl C command in terminal to end the mjpg-streamer server

Step 8: To combine webiopi and mjpg-streamer into same webpage which allows we “see” video from camera and control Robot Car with brower, we need change some default setting of WebIOPi and MJPG-streamer. To do so, we need to edit config file by typing following command and modify this file as Modification A, Modification B, Modification C:(skip this step if your micro SD card has pre-installed Osoyoo Robot Image)

sudo nano /etc/webiopi/config

Modification A: replace webiopi default script python file which allow us to send control signal to Pi from Browser, please add following pink line into “/etc/webiopi/config” file

[SCRIPTS]
# Load custom scripts syntax :
# name = sourcefile
#each sourcefile may have setup, loop and destroy functions and macros
#myscript = /home/pi/WebIOPi-0.7.1/examples/scripts/macros/script.py
myscript = /home/pi/osoyoo-robot/cam-robot/robot/script.py

Modification B. change webiopi default html file path by adding following pink line:

# Use doc-root to change default HTML and resource files location
#doc-root = /home/pi/WebIOPi-0.7.1/examples/servo-control
doc-root = /home/pi/osoyoo-robot/cam-robot/robot

Modification C. Add PCA9685 address into config by addling following pink line

[DEVICES]]
# Device configuration syntax:
# name = device [args...]
# name   : used in the URL mapping
#device : device name
#args   : (optional) see device driver doc
#If enabled, devices configured here are mapped on REST API /device/name
#Devices are also accessible in custom scripts using deviceInstance(name)
#See device driver doc for methods and URI scheme available

# Raspberry native UART on GPIO, uncomment to enable
# Don't forget to remove console on ttyAMA0 in /boot/cmdline.txt
# And also disable getty on ttyAMA0 in /etc/inittab
#serial0 = Serial device:ttyAMA0 baudrate:9600

# USB serial adapters
#usb0 = Serial device:ttyUSB0 baudrate:9600
#usb1 = Serial device:ttyACM0 baudrate:9600

#temp0 = TMP102
#temp1 = TMP102 slave:0x49
#temp2 = DS18B20
#temp3 = DS18B20 slave:28-0000049bc218

#bmp = BMP085

#gpio0 = PCF8574
#gpio1 = PCF8574 slave:0x21

#light0 = TSL2561T
#light1 = TSL2561T slave:0b0101001

#gpio0 = MCP23017
#gpio1 = MCP23017 slave:0x21
#gpio2 = MCP23017 slave:0x22
pwm0 = PCA9685 slave:0x40
#pwm1 = PCA9685 slave:0x41

#adc0 = MCP3008
#adc1 = MCP3008 chip:1 vref:5
#dac1 = MCP4922 chip:1

Finally, press “ctrl” + “x” and then “y” to save the file and press “enter” exist nano editor

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Step 9:Testing

Now you can put your car on the ground and turn on the power-switch in battery box. We need to use SSH to control the car. So you must enable SSH with raspi-config command before testing. If you are using windows, please use download Putty to ssh your Pi, if you are using MacBook, please directly use ssh command in terminal.

1. To start mjpg-streamer, in ssh terminal, please type followinig command:
cd ~/osoyoo-robot/cam-robot/mjpg-streamer
sudo ./start.sh

2. To start webiopi, please open another ssh window and type following command:
sudo webiopi -d -c /etc/webiopi/config

Now you can use your browse to acess Raspberry IP with port 8000(i.e, if your Pi IP address is 192.168.0.115, please visit http://192.168.0.115:8000, you will see following picture in your browser, click arrow buttons, you can make car moving to your desired directions.

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Android App

You can also use our free Android App instead of browser to control the car. Download the app from http://osoyoo.com/driver/osoyoo-robot.apk

Run the App, click set up and enter config page set the fields as following:

Robot IP:

your raspberrr pi ip Port: 8000
Video URL: http://your_raspberry_pi_ip:8899/?action=stream(please use IP such as 192.168.0.16 to replace your_raspberry_pi_ip)
User Name: webiopi
Password: raspberry

Click Save button and exit config page

Now you can use the arrow buttons in App to control the car

Byamber

Raspberry Pi Robot Car DIY learning Kit Package Listing

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Tutorial Lessons

Packing List:

Parts and Devices

Device

Picture
Qty.


Accessories

Raspberry Pi 3 Board

(Not in Package)

1 M2.5*5 Plastic Screw x 4
M2.5 Plastic Nut x 4
M2.5*5+6 Plastic Pillar x 4
OSOYOO Model-Pi Motor Driver Module
1 M3*30 Copper Pillar x4
M3*10 Screw x4
M3 Nut x4
M3 washer x4
PCA9685 compatible module
1
M2.5*5 Plastic Screw x 4
M2.5 Plastic Nut x 4
M2.5*5+6 Plastic Pillar x 4
Camera with mount holder
1
M3*10 Screw x2
M3 Nut x 2
Voltage Meter
1
M2.5*5 Plastic Screw x 2
M2.5 Plastic Nut x 2
M2.5*5+6 Plastic Pillar x 2
Tracking Sensor Module
5
M2.5*5 Plastic Screw x 5
M2.5 Plastic Nut x 5
M2.5*5+6 Plastic Pillar x 5
Car Chassis
1
M3*55 Copper Pillar x4
M3*10 Screw x8
M3 washer x8
Motors with wires
2

Metal Motor Holders x2

Wheels
2

Universal Wheel

1 M3*10 Screw x2
M3 Nut x2
M3 Washer x2
18650 Battery Box
with 2Pin
connectors
1 M3*10 Screw x 4
M3*10 Nut x 4
L USB port to Micro USB port cable
1

Connect Model-Pi Motor Driver Board with Raspberry Pi board

Camera cable
1

Connect Camera with Raspberry Pi board

5Pin 20cm Jumper wire 1 Connect 5 tracking sensor modules with Raspberry Pi board
4Pin 20cm jumper wire 1 Connect PCA9685 compatible module with Raspberry Pi board
2Pin 20cm jumper wire 1 Connect PCA9685 compatible module with Raspberry Pi board
3pin 15cm jumper wire 1 Connect voltage meter with Model-Pi motor driver board
4Pin 10cm jumper wire 1 Connect PCA9685 compatible module with Model-Pi motor driver board
2pin 10cm jumper wire 1 Connect PCA9685 compatible module with Model-Pi motor driver board
1 to 5pin female
jumper wire
2 Connect 5 tracking sensor modules with PCA9685 compatible module
HDMI to HDMI Cable
1
Metal Motor Holders
2
Srews Package
1
SD Card Reader
1
16GB TF card
1
Phillips Screwdriver
1
Slot Type Screwdriver
1
Cable Tie 10
Black electrician tape 1
Byamber

Raspberry Pi Robot Car DIY learning Kit Tutorial Guide

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Instroduction

There are many entry level Robot Car Kits in the market, most of them are controlled by Arduino Boards. You can check our tutorial blog for such Arduino Robot kit in http://osoyoo.com/2017/08/06/osoyoo-robot-car-diy-introduction .

The advantage of Arduino Robot Car kit is that Arduino has no Operation System and programming is simple and easily. For some basic robot application which needs only simply logic to handle sensor data and control actuators, Arduino-controlled robot car is a good choice.

However, for some more complex robot applications which need more complex functions such as computer vision(CV), Internet of Things (IoT), web server control etc, Arduino board’s ability is too weak to reach the target.

In order to help intermediate students to complete some complex Robotic project. We developed a more advanced Raspberry Pi Robot Car learning Kit.


Why Raspberry Pi is so important to the Robot Car DIY learning kit?

Because Raspberry Pi is a real computer which has Linux OS(Raspbian) and therefore much powerful than Arduino Board which is simply a micro-controller(MCU).

With Raspbian OS and its huge open-source software community , people can make much complicated Robot projects,i.e web appliation, database, A.I, machine learning, IoT, Computer Vision etc.

Unlike Arduino board, Raspberry Pi programming environment is much more complex and flexible. It supports almost all programming language as long as the language is supported by Rasbian Open Source community. The most commonly used languages for access Raspberry Pi GPIO pins are C and Python. If you want to learn some Raspberry Pi hardware GPIO programming, you can read our tutorial in following links:

http://osoyoo.com/2017/10/09/raspberry-pi-starter-kit-v1-introduction/

http://osoyoo.com/2016/06/13/internet-of-thingsiot-starter-kit-on-raspberry-pi/

Since Raspberry Pi programming is different from Arduino, we suggest user should get some basic Linux knowledge before practice Raspberry Pi Robot project.


If you want to learn Linux Robot by doing, you can buy this kit as learning kit. We provide some basic lessons in the kit to show you how to set up Rasbian Linux environment, how to use Linux shell to control car movement and how to use web browser to monitor and control car movement through the camera.

These basic projects in our tutorial have step by step instruction with sample code, circuit graph and installation video.These lessons all have been tested, so if you strictly follow our instruction, they will work without any problem. We also write detailed comments in our python sample code which can help you to understand the code and customize for your own application. However, you must have some linux and python background knowledge otherwise please do not change the code.

We also provide an optional Open-CV sample project for use to practice Robotic Computer Vision procedure. However, as OPENCV and machine learning open source community is evolving everyday, we can not guarantee that the opencv project will work properly. You might do your due diligence to follow up the opencv community’s updates and make your project work.

If you have any interesting application to use our Robot kit, you are more than welcome to share your excellent ideas in our comments section.

Tutorial Directory

Raspberry Pi Robot Car Lesson 1:
Basic Framework Installation

Raspberry Pi Robot Car Lesson 2:
Line Follow

Raspberry Pi Robot Car Lesson 3:
Web Control Camera
Packing List
Packing List
Byamber

Transistor Tester User Guide

I  Introduction

This meter is an intelligent semiconductor device analyzer, it can measure most of the diodes, bipolar transistors, Junction/MOS FETs and low power thyristors. It automatically identifies the type of devices and pin outs, measures the current gain HFE, gate threshold and FET junction capacitance, a typical application is to pair two transistors or identifies an unknown SMD device. The test clips can be connected any way round, the pin out can be identified and displayed on screen vs. test clip numbers. Beside the semiconductor device analyzer, this meter can also work as an ESR meter, the ESR accuracy may not be able to compete with the professional one, but it definitely meets the needs for most of the applications.

 

II  Specification

Working power: DV 9V

Standby current: 0.02uA

Operating current: 25mA

Resistor Range: 0.1Ω-50MΩ

Capacitor Range: 25pF-100000uF

Inductance Range: 0.01mH – 20H

Instructions

  1. There are some digit codes like 1, 2, and 3 on back of test jig. Insert the DUT on test jig and press the button to start, the meter will identify and display the pin out vs. the clip numbers on the screen.
  2. When the DUT has two pins, you can choose different jig combination as test terminal, i.e. 1-2, 1-3 or 2-3.When the DUT has polar, the polar can be detected and shown accordingly.
  3. When the DUT has three pins, you can choose different triple-jig combinations as test terminal, i.e. 1-2-3, 2-3-1 or 3-2-1.

III  Features

  1. Operates with ATmega328 microcontrollers.
  2. One key operation with automatic power shutdown.
  3. Shutdown current is only about 20nA.
  4. Automatic detection of NPN and PNP bipolar transistors, N- and P-Channel MOSFETs, JFETs, diodes, double diodes, Thyristors and Triacs.
  5. Automatic detection of pin layout of the detected part.
  6. Measuring of current amplification factor and Base-Emitter threshold voltage of bipolar transistors.
  7. Darlington transistors can be identified by the threshold voltage and high current amplification factor.
  8. Detection of the protection diode of bipolar transistors and MOSFETs.
  9. Measuring of the Gate threshold voltage and Gate capacity value of MOSFETs.
  10. Up to two Resistors are measured and shown with symbols and values with up to four decimal digits in the right dimension. All symbols are surrounded by the probe numbers of the Tester (1-3). So Potentiometer can also be measured. If the Potentiometer is adjusted to one of its ends, the Tester cannot differentiate the middle pin and the end pin.
  11. Resolution of resistor measurement is now up to 0.01_, values up to 50M_ are detected.
  12. One capacitor can be detected and measured. It is shown with symbol and value with up to four decimal digits in the right dimension. The value can be from 25pF to 100mF. The resolution can be up to 1pF.
  13. For capacitors with a capacity value above 2μF the Equivalent Serial Resistance (ESR) is measured with a resolution of 0.01_ and is shown with two significant decimal digits.
  14. Up to two diodes are shown with symbol or symbol in correct order. Additionally the flux voltages are

shown.

  1. LED is detected as diode; the flux voltage is much higher than normal. Two-in-one LEDs are also detected as two diodes.
  2. Zener-Diodes can be detected, if reverse break down Voltage is below 4.5V. These are shown as two diodes, you can identify this part only by the voltages. The outer probe numbers, which surround the diode symbols, are identical in this case. You can identify the real Anode of the diode only by the one with break down

(threshold) Voltage nearby 700mV!

  1. Only one measurement is needed to find out the connections of a bridge rectifier.
  2. Capacitors with value below 25pF are usually not detected, but can be measured together with a parallel diode or a parallel capacitor with at least 25pF. In this case you must subtract the capacity value of the parallel connected part.
  3. For resistors below 2100also the measurement of inductance will be done, if your ATmega has at least 16K flash memory. The range will be from about 0.01mH to more than 20H, but the accuracy is not good. The measurement result is only shown with a single component connected.
  4. Thyristors and Triacs can only be detected, if the test current is above the holding current. Some Thyristors and Triacs need as higher gate trigger current, than this Tester can deliver. The available testing current is only about 7mA!

 

IV  Special Caution:

  1. Discharge the capacitors completely before you measure it, otherwise, it could damage your meter.
  2. Considering the accuracy of testing, please replace batteries when battery power is low.
  3. Brightness Adjustment: Keep pressing the power button and enter into the interface of contrast adjustment.
  4. Error Correction: Please prepare your own necessities and refer to the following procedure.

Calibration Method:

1) Turn off the meter. Use 2 wires to shortcircuit the little metal sheet marked with 1, 2 and 3; don’t release the shortcircuit wires until step 3.

2) Push the start button to turn on the meter. The screen will show self test mode, the 2nd line will show ? Mark. Push the start button again quickly and Calibration will start.

3) When screen shows T4 isolate Probe, remove the shortcircuit wires.

4) When screen shows 1-II-3 >100nf, connect a non-polar capacitor (>100nf) to the meter, the calibration procedure will keep going until completion.

V  Test examples

1.

It shows that no device is connected on test terminals or an unknown part. It may also be that the devise was damaged.

 

 

  1. Test a triac

It shows that the DUT is a triac, test terminals 1, 2 and 3 are connected to control gate G, anode A, Anode K.

 

 

  1. Test a diode

It shows that the DUT is a diode, test terminal 1 is connected to cathode, and test terminal 2 is connected to anode.The forward voltage is 1.91mV. Junction capacitance is 4pF.

 

  1. Test a capacitor

It shows that the DUT between terminal 2 and 3 is a capacitor. Capacitance =991.7uF, ESR=0.02 ohm and Voltage loss is 1.5%.

 

 

  1. Test a resistor

It shows the DUT is an 82.57k resistor, between terminal 1 and 2.

 

 

 

  1. Test a MOS FET

It shows that the DUT is PMOS FET, test terminals 1, 2 and 3 are connected to pin S, D and G. There is a protect diode between S and D, the anode of the diode is connected to D, and the cathode of the diode is connected to S.Junction capacitance is 673pF; the gate threshold voltage is 3.05V..