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Chinese version of the README -> please click here

Dobot TCP-IP-4Axis-Python-CMD secondary development API interface ( TCP-IP-MG400-Python Chinese README )

1. Introduction

TCP-IP-4Axis-Python is a software development kit designed by Dobot based on Python of TCP/IP protocol. It is developed based on Python language, follows the Dobot-TCP-IP control communication protocol, connects to the device terminal via Socket, and provides users with an easy-to-use API interface. Through TCP-IP-4Axis-Python, users can quickly connect to the Dobot device and carry out secondary development to control and use the device.

Pre-dependency

• You can connect your computer to the network interface of the controller with a network cable, and then set the fixed IP to be in the same network segment as the controller IP. You can also connect your computer to the controller via wireless connection.

  When connected to LAN1 via wired connection: IP: 192.168.1.6;
  When connected to LAN2 via wired connection: IP: 192.168.2.6;
  Wireless connection: IP: 192.168.9.1

• Try pinging the controller IP to make sure it is under the same network segment.

• Setup the Python environment. For details, please refer to Python Setup and Usage.

  Python configuration: pip install numpy

• This API interface and Demo are applicable to V1.5.6.0 and above controller version of MG400/M1Pro series

Version and Release

Current version V1.0.0.0

Version	Date
V1.0.0.0	2023-03-07

2. Technical support

3. TCP-IP-4Axis-Python control protocol

As the communication based on TCP/IP has high reliability, strong practicability and high performance with low cost, many industrial automation projects have a wide demand for controlling robots based on TCP/IP protocol. Therefore, the MG400/M1Pro robot is designed to provide rich interfaces for interaction with external devices based on the TCP/IP protocol. For more details, see TCP_IP Remote Control Interface Guide (4axis).

4. Obtaining TCP-IP-4Axis-Python

1. Obtain the secondary development API program of Dobot TCP-IP-4Axis-Python-CMD from GitHub.

   `git clone https://github.com/Dobot-Arm/TCP-IP-4Axis-Python.git

2. Refer to the corresponding README.md file for use.

5. File and class descriptions

1. main.py: The running entrance of the main program.

2. dobot_api.py: encapsulate the robot interface. For details, refer to the TCP_IP Remote Control Interface Guide (https://github.com/Dobot-Arm/TCP-IP-Protocol).

3. files: Files related to the alarm ID, alarm_controller.json: Warning alarm profile, alarm_servo.json: Servo alarm profile

4. PythonExample.py: Contains usage and code examples of some API interface commands.

Class descriptions:

Class	Define
DobotApi	Interface class based on TCP communication, encapsulates the basic business of communication
DobotApiDashboard	Inherited from DobotClient, it implements the specific basic functions of the robot
DobotApiMove	Inherited from DobotClient, it implements the specific motion functions of the robot
MyType	Data type, it feeds back the robot status list
alarm_controller	Warning alarm configuration information
alarm_servo	Servo alarm configuration information

DobotApi

Interface class based on TCP communication, encapsulates the basic business of communication.

class DobotApi:
    def __init__(self, ip, port, *args):
    ""
    if self.port == 29999 or self.port == 30003 or self.port == 30004:
            try:
                self.socket_dobot = socket.socket()
                self.socket_dobot.connect((self.ip, self.port))
    ""        

DobotApiDashboard

Inherited from DobotClient, it can deliver some settings-related commands to the robot. It implements the specific basic functions of the robot.

class DobotApiDashboard(DobotApi):
    """
    Define class dobot_api_dashboard to establish a connection to Dobot
    """
    def EnableRobot(self,*dynParams):
      """

DobotApiMove

Inherited from DobotClient, it can deliver some motion-related commands to the robot. It implements the specific motion functions of the robot.

class DobotApiMove(DobotApi):
    """
    Define class dobot_api_move to establish a connection to Dobot
    """
    def MovJ(self, x, y, z, r,*dynParams):

MyType

Data type, it feeds back the robot status.

MyType=np.dtype([('len', np.int16, ), 
                ('Reserve', np.int16, (3,) ),

Create control port, motion port, and feedback port respectively for TCP connection.

    ip = "192.168.1.6"
    dashboardPort = 29999
    movePort = 30003
    feedPort = 30004
    print("Connecting...")
    dashboard = DobotApiDashboard(ip, dashboardPort)
    move = DobotApiMove(ip, movePort)
    feed = DobotApi(ip, feedPort)
    

Deliver control commands via control port to enable or disable the robot.

     dashboard.EnableRobot()
     dashboard.DisableRobot()

Deliver motion commands via motion port to control the motion of the robot.

    x=10
    y=10
    z=10
    r=10
    move.MovL(x,y,z,r)
    move.MovJ(x,y,z,r)

Get the robot status via the feedback port.

    data = bytes()
    while hasRead < 1440:
        temp = feed.socket_dobot.recv(1440 - hasRead)
        if len(temp) > 0:
            hasRead += len(temp)
            data += temp
    hasRead = 0
    feedInfo = np.frombuffer(data, dtype=MyType)
    if hex((feedInfo['test_value'][0])) == '0x123456789abcdef':
        print(feedInfo['EnableStatus'][0])   #Output device enabling status

For details, see the PythonExample.py and the Demo example.

6. Common problem

Problem 1: TCP connection. Port 29999/30003 cannot be connected or cannot deliver commands after connecting.

Solution: If the controller version is below V1.6.0.0, you can try to upgrade the controller to V1.6.0.0 or above. If the controller version is already V1.6.0.0 or above, you can feedback the problem to technical support.

Problem 2: During TCP connection, the 29999 control port can send commands, but the 30003 motion port cannot send commands.

Solution: If motion queue is blocked, you can try to reopen the queue by delivering clearerror() and continue() commands via port 29999.

Problem 3: How to judge whether the robot motion command is in place or not

Solution: It can be judged by delivering a sync command.

It can be judged by comparing the Cartesian coordinates of the target point with the actual Cartesian coordinates of the robot.

7. Example

• Dobot-Demo realizes TCP control of the robot and other interactions. It connects to the control port, motion port, and feedback port of the robot respectively. It delivers motion commands to robot, and handles the abnormal status of the robot, etc.

1. Main thread: Connect to the control port, motion port, and feedback port of the robot respectively. Enable the robot.

2. Feedback status thread: Real-time feedback of robot status information.

3. Robot motion thread: Deliver motion commands to robot.

4. Exception handling thread: Judge and handle the abnormal status of the robot.

Steps to run the Demo:

1. Obtain the secondary development API program of Dobot TCP-IP-4Axis-Python-CMD from GitHub.

   `git clone https://github.com/Dobot-Arm/TCP-IP-4Axis-Python.git

2. Connect to the robot via LAN1 interface, and set the local IP address to 192.168.1.X.

   Control Panel >> Network and Internet >> Network Connections.

   

   Select the connected Ethernet >> Right click >> Properties >> Internet Protocol Version (TCP/IPV4).

   Modify the IP address to 192.168.1.X.

   

3. Open the DobotStudio Pro, connect to the robot, and set the robot mode to TCP/IP secondary development.

   

4. To run the program, you need to detect the dynamic library, open the whole directory in VsCode/PyCharm and run main.py directly.

   

Common problem

Problem 1: ModuleNotFoundError : Nomode name 'numpy'

Solution: If the numpy environment is not installed, install numpy pip install numpy.

Problem 2: Cartesian coordinates of different models (MG400/M1pro) in Demo

Solution: Confirm the Cartesian coordinates of the model and modify the coordinates in Demo.

Make sure the robot is in a safe position before running the Demo to prevent unnecessary collisions