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Tutorials

Rider-Pi Two Wheel-legged Robot

Rider-Pi is a desktop two wheel-legged robot designed for developers, educators and robot enthusiasts. Built-in inertial measurement unit (IMU) and the carbon fiber connecting rod structure, which allow the robot to adjust the joint angle in real time to adapt to different terrain obstacles. Based on the Raspberry Pi CM5 core module, adopt Python programming, support a series of AI functions such as face recognition, color tracking/following, QR code motion control, object detection, license plate recognition, gesture following, etc. A 2.0-inch IPS screen on the front, can display video images and 35 dynamic expressions in real time. In addition, Rider-Pi also supports ChatGPT (extra charge), which can realize voice Q&A, voice control, text-to-picture, and image analysis description functions.

Features

1) Based on the Raspberry Pi CM5 module, uses Python programming, with better computing performance and wider development support.

2) High-precision IMU module and connecting rod bipedal structure, it has both the mobility of wheeled robots and the obstacle crossing ability of legged robots.

3) Equipped with a 2.0-inch IPS display, it can flexibly display 35 dynamic expressions.

4) Can realize face recognition, object detection, gesture recognition, license plate recognition, QR code control, etc.

5) Two remote control methods: Bluetooth and WiFi APP(Android/iOS) be provided for free.

6) Supports ChatGPT (extra charge), which can realize voice Q&A, voice control, text to picture, image analysis description, etc.

 

 

Rider-Pi Two Wheel-legged Robot(Raspberry Pi CM5 core module)

Vendor: Yahboom

SKU: 3000200895

Regular price $519.00 USD
Version: CM5
In stock, ready to be shipped

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Tutorials

Rider-Pi Two Wheel-legged Robot

Rider-Pi is a desktop two wheel-legged robot designed for developers, educators and robot enthusiasts. Built-in inertial measurement unit (IMU) and the carbon fiber connecting rod structure, which allow the robot to adjust the joint angle in real time to adapt to different terrain obstacles. Based on the Raspberry Pi CM5 core module, adopt Python programming, support a series of AI functions such as face recognition, color tracking/following, QR code motion control, object detection, license plate recognition, gesture following, etc. A 2.0-inch IPS screen on the front, can display video images and 35 dynamic expressions in real time. In addition, Rider-Pi also supports ChatGPT (extra charge), which can realize voice Q&A, voice control, text-to-picture, and image analysis description functions.

Features

1) Based on the Raspberry Pi CM5 module, uses Python programming, with better computing performance and wider development support.

2) High-precision IMU module and connecting rod bipedal structure, it has both the mobility of wheeled robots and the obstacle crossing ability of legged robots.

3) Equipped with a 2.0-inch IPS display, it can flexibly display 35 dynamic expressions.

4) Can realize face recognition, object detection, gesture recognition, license plate recognition, QR code control, etc.

5) Two remote control methods: Bluetooth and WiFi APP(Android/iOS) be provided for free.

6) Supports ChatGPT (extra charge), which can realize voice Q&A, voice control, text to picture, image analysis description, etc.

 

 

Questions & Answers

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  • Hi, I would like to improve the speed of local AI applications. Is it possible to mount on rider pi an AI hat accelerator or some hardware to speed up operations ?

    Hello,

    We are sorry, but we do not currently have any such case studies.

    If you have any other questions, please email us at support@yahboom.com

    Have a great day!

  • Hi, I’m using a Rider-Pi CM5 and would like to expand it with a LiDAR sensor for navigation (UART or USB). Is this possible, and are there specific LiDARs that work well with this platform? Thanks !

    Hello,

    Thank you for your patience.

    The LiDAR sensor cannot be installed on the Rider-Pi CM5.

    Thanks for your understanding.

    Have a great day!