myCobot 320 M5

1 Profile

Updated from myCobot 280, myCobot 320 M5 can be redeveloped depending on users\' demands with delicate structure and all-in-one design. myCobot 320 for M5 weights 3kg with a load of 1kg and working radius of 320mm. The small-sized product is endowed with powerful functions and is characterized by easy operation, and the ability to work with human safely.

2 Product Parameters

3 Product Performance

• Easy to operate and open-source
  • Users can operate the robot via myBlockly and dragging teaching easily after quick-start learning.
  • It supports the development systems, such as ROS and moveIt.
• Economical and cost-effective
  • It adopts a standardized 8-hour working system so as to replace human in doing repetitive and standard jobs.
  • Worth over 10,000 RMB, it reduces costs and synergizes efforts for high-efficiency scientific research.
• Powerful performance and equipped with two screens
  • It adopts a brushless DC servo so as to realize repeated positioning precision of ±0.5mm.
  • The body is equipped with two screens and supports M5 ecological applications, effectively expanding coordinative application.
• On-in-all design and safe collaborative work
  • With delicate structure, it optimizes space and integrates with application in a coordinated way.
  • It also has kinematics self-interference detection, which can effectively avoid motion collisions.

4 Application Scenarios

myCobot 320 M5 is not only a tool for production but also a tool to expand imagination boundary. It means it can work with multiple types of end effectors to adapt to a variety of application, such as scientific research, education and function showing, etc. The user experience is excellent.

5 Development Support

• 3 Quick learning of robot arm knowledge
  • 3.1 Serial robot
  • 3.2 Electronic background knowledge
  • 3.3 Mechanics background knowledge
  • 3.4 Knowledge of motor and servo
• 4 Basic function application
  • 4.1 myStudio
    • 4.1.1 Installing driver
    • 4.1.2 Updating equipment firmware
  • 4.2 Factory firmware introduction
    • 4.2.1 Drag teaching
      • 4.2.1.2 Microprocessor class
    • 4.2.2 Zero point calibration
      • 4.2.2.2 Microprocessor class
    • 4.2.3 Communication forwarding
      • 4.2.3.2 Microprocessor class
    • 4.2.4 Connection Detection
      • 4.2.4.2 Microprocessor class
  • 4.3 Use for the first time
• 5 Blockly Development Guide
  • 5.1 myblockly
    • 5.1.1 Controlling the RGB light board
    • 5.1.2 Controlling the robot arm to make it return to the origin
    • 5.1.3 Controlling single-joint motion
    • 5.1.4 Controlling multiple joints
    • 5.1.5 Controlling the robot arm to make it sway left and right
    • 5.1.6 Controlling the robot arm to make it dance
    • 5.1.7 Gripper installation and use
    • 5.1.8 Installation and use of sucking pump
• 6 Roboflow Development Guide
  • 6.1 Environment building
  • 6.2 Simple use
  • 6.3 Joint control & coordinate control
  • 6.4 IO control
  • 6.5 Gripper control
  • 6.6 MODBUS
• 7 Python Development Guide
  • 7.1 Environment building
  • 7.2 Joint control
  • 7.3 Coordinate control
  • 7.4 IO control
  • 7.5 Gripper control
  • 7.6 TCPIP
  • 7.7 Use cases
  • 7.8 API Description
• 12 ROS Development Guide
  • 12.1 Introduction
  • 12.2 Environment building
  • 12.3 ROS Basics
  • 12.4 Introduction and use of rviz
  • 12.5 moveit
• 13 Use of senior packages
  • 13.1 Introduction
  • 13.2 Environment
  • 13.3 Knowledge preparations
  • 13.4 Color recognition
  • 13.5 Image recognition
  • 13.6 Aruco code recognition
• 14 FAQ
  • 14.0 How to ask questions gracefully
  • 14.1 Driver-related
  • 14.2 Software
  • 14.3 Hardware