MyCobot artificial intelligence kit is an entry-level artificial intelligence suite integrating vision, positioning and grabbing, and automatic sorting modules. Based on the Linux system, build a 1:1 simulation model in ROS, which can realize the control of the robotic arm through the development of software. It is simple and easy to learn. It can quickly learn the basics of artificial intelligence, inspire innovative thinking, and comprehend the open-source creative culture.
The suit has good scalability and high openness and can be used for multiple purposes. It is easy to use the training platform of colleges and universities, the construction of robotics disciplines, the robotics laboratory, or personal learning and use.
Aruco code detection and tracking: precise positioning and calibration of the camera, and automatic capture.
Color and image recognition: Using deep learning algorithms, users can use robotic arms to complete positioning, grabbing, and automatic sorting.
What can you learn?
- Python programming
- 6 DOF robot control principle
- End-effector control
- AI machine vision and artificial intelligence
- LCD display control
- Smart sensor detection (color, image, aruco code)
Rich teaching Demo, intuitive and efficient
With rich teaching demos such as color recognition, image recognition, and aruco code recognition, it helps users to understand the basic composition and working principle of the robot artificial intelligence vision kit more clearly and intuitively.
Artificial Intelligence Kit
- Material box
- Trash Bins
- Artificial intelligence kit_ Bottom Plate
- Material box stand
- Square (provide sticker)
- Suction Pump
- Vision module_ Base stand
- Vision module_ camera
- Vision module_ Camera flange
- Vision module_ Camera bracket
- Vision module_ Fibre tube
- Suction pump connecting line_ Power distribution
- Suction pump connecting line_ power cord
- Suction pump connecting line_ DuPont line
Name – USB non-distortion lens
Size – 18X18X20mm
Maximum pixels – 1 million 1280X720
Support image formats – YUV, MJPEG
Pixel size – 3.4umX3.4um
Maximum frame rate – 1280×720 @ 25fps
Supported resolution – 1280X720, 640X480, 320X240
Power supply – DC5V 90mA
Lens focal length – standard 1.7mm
Field of view angle – ≈60°
Supported systems – Win7/8/10, Linux, MAC
USB protocol – USB2.0 HS/FS