Elephant Robotics focuses on promoting industry talent development in artificial intelligence and robotics. Our Artificial Intelligence (AI) Educational Laboratory Solution aims to provide students with the most comprehensive Robotics and AI discipline experience, including laboratory equipment and teaching content.
Laboratory Equipment
We provide students with the latest robot hardware, software, and control system equipment to ensure that they can conduct experiments and research in a real-world environment.
- Embedded Raspberry Pi ecosystem, development-oriented secondary development system ecosystem.
- Comes with ROS and ROS2, graphical programming with Blockly.
- Image recognition function, with built-in image recognition algorithms, optional with any camera, and can be matched with different accessories such as monitors, grippers, and suction pumps to achieve multiple application scenarios.
- High configuration, with LEGO interface.
- Integrated design, easy to carry.
- Can perform openCVD, Python programming, inverse kinematics, robot control, machine vision, end effector usage.
Robotics and Artificial Intelligence Textbook
The textbook is designed to provide students with the opportunity to learn about artificial intelligence robotics. Students will learn about the working principles of robots and the basics of robot visual recognition. By combining these two areas of knowledge, students will be able to develop applications for robotic automation, including automatic recognition and grasping.
The course covers a range of interdisciplinary and diverse principles, including: robot component modules, coordinate system concepts, the relationship between linkages and joints, robot forward kinematics, robot inverse kinematics, robot dynamic modeling, trajectory planning for robot motion, python-driven robot applications, multi-sensor fusion applications, computer vision principles and applications, and hand-eye coordination applications.
Technical Parameters
mechArm 270 PI Robotic Arm
| Degree of Freedom |
6 |
| Working radius（mm） |
270mm |
| Payload（g） |
250g |
| Weight（g） |
1000g |
| Repeatability（mm） |
±0.5mm |
| Maximum joint speed |
120°/s |
| Power interface INPUT |
DC8.4V-14V |
| Mechanical Arm Configuration |
Center symmetric structure |
| Motor Type |
High-precision magnetic encoder motor * 6 |
| Control |
Raspberry Pi 4B, 1.5GHz 4-core processor, running Debian/Ubuntu |
|
AI Kit 2023
| Recognition Speed |
Color/Shape/QR Code: 300ms |
| Feature Point |
600ms |
| Recognition Accuracy |
≤3mm |
| Camera |
USB distortion-free camera |
| Image Pixel |
2M 1080p |
| Supported Image Formats |
MJPG/YUY2 |
| Pixel Size |
3.0umx3.0um |
| Maximum Frame Rate |
MJPG: 19201080@30fps YUV: 19201080@30fps |
| USB Protocol |
Standard UVC Protocol |
| Power Supply |
DC5V 90mA |
| PField of View Angle |
110° without distortion |
| Lens Focal Length |
2.8mm |
| Supported Systems |
Windows XP/7/8/10/VISTA/SEVEN/MAC LINUX(include uvc)/Raspberry Pi/Android 4.2+ |
KIT COMPONENTS
|
|
]]>
