Overview
Rider-Pi is a desktop two wheel-legged robot designed for developers, educators, and robot enthusiasts. It is based on the Raspberry Pi CM5 core module and uses Python programming. With a built-in inertial measurement unit (IMU) and a carbon fiber connecting rod structure, the robot can adjust joint angles in real time to adapt to different terrain obstacles. A 2.0-inch IPS screen on the front can display video images and 35 dynamic expressions in real time.
Key Features
- Raspberry Pi CM5 core module + Python development: Designed for wider development support.
- Wheel-legged linkage structure: Combines wheeled mobility with legged obstacle-crossing capability; supports forward/backward movement and 360° rotation.
- IMU posture stabilization: Adjusts robot posture in real time to adapt to various terrain obstacles.
- 2.0-inch IPS color display: Supports video display, 35 dynamic expressions, and custom dynamic expressions.
- Vision + interaction hardware: Integrated 5MP HD camera, digital microphone (also described as dual MEMS digital microphones), speaker(s), and four programmable buttons.
- AI visual recognition & interaction examples: Face detection, face tracking, emotion recognition (CM5 version), 3D object recognition, target detection, object detection, license plate recognition, color tracking/following, gesture following/control, QR code motion control, human skeleton recognition, palm control, face mask, and brush (finger drawing on the screen).
- Pre-installed GUI program: Includes 30+ functions to quickly experience core features.
- Remote control methods: Bluetooth and WiFi app (Android/iOS) are provided for free.
- ChatGPT support (extra charge): Enables voice Q&A, voice control, text-to-picture, and image analysis description functions.
- Actuation components shown: Micro integrated wheel hub motor; all-metal magnetic encoding bus serial port servo.
Specifications
| Product | Rider-Pi Two Wheel-Legged Robot |
| Main control | Raspberry Pi CM5 core module (also stated to support Raspberry Pi CM4 and CM5) |
| Programming | Python |
| Display | 2.0-inch IPS color display |
| Expressions | 35 dynamic expressions; supports custom dynamic expressions |
| Camera | Integrated 5MP HD camera |
| Audio | Digital microphone (also described as dual MEMS digital microphones); speaker(s) |
| Buttons | Four programmable buttons |
| Sensor | Built-in inertial measurement unit (IMU) |
| Remote control | Bluetooth; WiFi app (Android/iOS) |
| CM4 vs CM5 (as provided) |
CM4: BCM2711 SoC; 4-core 64-bit Arm Cortex-A72; 1.5GHz; GPU: VideoCore VI; Memory: 2GB CM5: BCM2712 SoC; 4-core 64-bit Arm Cortex-A76; 2.4GHz; GPU: VideoCore VI; Memory: 2GB |
Applications
- Python robotics learning and classroom demonstrations
- AI vision experiments: object detection, face detection/tracking, 3D object recognition, license plate recognition, color tracking/following
- Human interaction demos: gesture following/control, palm control, human skeleton recognition, voice interaction (including optional ChatGPT features)
- QR code motion control demonstrations
Tutorials
The following video is provided for function demonstrations and learning:
Support
For pre-sales questions and after-sales support, contact https://rcdrone.top/ or email support@rcdrone.top.
Details

Rider-Pi pairs a Raspberry Pi CM5 core module with a wheel-legged chassis for agile desktop robotics and Python development.

Everything is built around the CM5 platform, with a compact form factor designed for learning, prototyping, and demos.

A wide set of demos and hardware highlights supports quick evaluation before deeper customization.

CM5 compute power, onboard camera/audio, and programmable buttons combine for vision projects and interactive control.

Real-time posture sensing helps maintain balance while rolling, turning, and handling small obstacles.

Multimodal interaction enables voice Q&A, voice control, and camera-based understanding workflows.

Use app-style examples to explore conversational commands and scene prompts in a robotics context.

Computer-vision demos cover detection, tracking, and recognition tasks suitable for classroom and lab experiments.

Hands-free interaction options include gesture-style control and tracking behaviors for responsive demos.

Built-in examples help validate camera workflows such as color following and QR-driven motion commands.

Gesture recognition can map hand signals to movement patterns for intuitive control without a controller.

Preset action groups make it easy to trigger polished movement routines from the mobile app.

A pre-installed GUI provides quick access to core demos, settings, and common vision/interaction modes.

Step-by-step tutorials support setup, programming workflows, and repeatable experiments.

The 2.0-inch IPS display supports real-time video and a library of expressive animated faces.

Core utilities include recording, lighting effects, posture readouts, battery monitoring, and motion controls.

Control Rider-Pi from iOS or Android over WiFi or Bluetooth, with app controls designed for quick testing.

A structured course outline helps guide learning from setup to advanced vision and interaction projects.

Rider-Pi includes organized learning folders for Quick Start, Raspberry Pi basics, car control and motion control, AI visual recognition and interaction, and voice interaction.

Rider-Pi includes a structured set of AI interaction lessons, English-subtitled operation videos, and open-source Python code for development.

The Rider-Pi robot is backed by a provided 3D model file for DIY modeling and professional after-sales technical service.

Rider-Pi uses a two wheel-legged linkage structure that combines wheeled mobility with a legged-style obstacle-crossing motion.

Rider-Pi uses an ABS body with carbon fiber accents, an aviation aluminum rear cover, and wear-resistant silicone contact points for durability.

The hub motor integrates a brushless motor, control circuit, and magnetic encoder for 360° control with peak torque up to 2 kg·cm.

The rider robot uses an all-metal servo design with reduction gears, built-in sensors, and integrated control circuitry for precise joint movement.

The robot driver expansion board provides dedicated connectors for servo/motor control, serial communication, power input, charging, a 5V fan, and RGB lighting.

Rider-Pi’s modular structure combines a Raspberry Pi CM5 module, 5MP camera, 2.0-inch IPS display, robot driver board, servos, hub motors, and an 18500 battery for assembly.

Rider-Pi uses a Raspberry Pi CM5 (2GB RAM) with ESP32 control, a 2.0-inch IPS 320×240 display, dual MEMS mic, 5MP OV5647 camera, and two 8.4V brushless hub motors.

The Rider-Pi CM5 robot uses a coreless servo motor (4.5KG·CM torque) and lists LAN TCP/BT communication, 572g weight, and 115×135×125mm dimensions (squatting).

The Rider-Pi wheel-legged robot package includes an assembled robot, TF card, USB-C data cable, USB-C hub, and a micro-to-HDMI cable.
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