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RDK X5 MagicBox📖
1.RDK MagicBox
  • 1. RDK MagicBox Official Materials
  • 2. Troubleshooting boot failure
  • 3. Linux memory query
2.RDK MagicBox Introduction
  • 1. Introduction to RDK MagicBox
  • 2. Write System File
  • 3. Hardware Interface Description
3.RDK MagicBox User Guide
1. Quick Start
  • Quick Start
2. Basic Peripheral Usage
  • Basic Peripheral Usage
3. Algorithm Development
  • 1. Stereo Depth Estimation
  • 2. Gesture Interaction
  • 3. Voice Interaction
4.RDK MagicBox Basic Settings
  • 1.Network configuration
  • 2.Remote login
  • 3.Update system
  • 4.srpi-config user guide
  • 5.config. txt configuration file
  • 6.Self-startup setting
  • 7.RDK exclusive command usage
  • 8.Linux command usage
  • 9.GPIO readwrite operation
  • 10.Image classification algorithm
  • 11.Use USB camera
  • 12.MIPI Camera Usage
5.RDKX5 Magicbox Basic Development Course
For C language
  • 1. Camera Image Acquisition and Display
  • 2. Camera Image Local Saving
  • 3. Camera Image Acquisition and Encoding
  • 4. Video File Decoding and Display
  • 5. RTSP Stream Decoding
  • 6. VPS Scaling Example
  • 7. Target Detection Algorithm — focs
  • 8. Target Detection Algorithm — YOLOv5s
  • 9. Using CAN
For Python language
  • 1. Prerequisites Before Using Pin Functions
  • 2. Using GPIO
  • 3. Using PWM
  • 4. Use serial port
  • 5. Using I2C
  • 6. Using SPI
For Linux Development
  • Linux Development Guide
6.Online AI Model Course
Online AI Model Course(Text Interaction)
  • 0. Preparation before use
  • 1. OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Application
  • 3. Multimodal Visual Positioning Application
  • 4. Multimodal Table Scanning Application
  • 5. Multimodal Autonomous Agent Application
Online AI Model Course(Voice Interaction)
  • 1. Online Speech‑to‑Text (ASR)
  • 2. Online Text‑to‑Speech (TTS)
  • 3. AI Large Model Voice Interaction
  • 4. Multimodal Visual Voice Interaction
  • 5. Multimodal Visual Positioning Application
  • 6. Multimodal Table Scanning Application
  • 7. Multimodal Autonomous Agent Application
  • 8. AI Large Model Online Voice Assistant
7.OpenClaw Embodied AI Development
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Deployment
  • 3. OpenClaw Whatsapp Plugin Application
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw TUI Interaction
  • 6. OpenClaw Tool Introduction
  • 7. OpenClawGate Gateway User Manual
  • 8. OpenClaw Plugin Feature Introduction
  • 9. OpenClaw ClawHub Introduction (skill installation)
  • 10. OpenClaw Application - File Management
  • 11. OpenClaw Application - Camera
  • 12. OpenClaw Application - Browser Control
  • 13. OpenClaw Application - Script Execution
  • 14. OpenClaw Application - AI‑programmed Status Light Control
  • 15. OpenClaw Application - AI‑programmed Servo Control
  • 16. OpenClaw Application - Dedicated AI Assistant
8.ROS2 Basic Tutorial
  • 1.Introduction to ROS2
  • 2.ROS2 install Humble
  • 3.ROS2 development environment
  • 4.ROS2 workspace
  • 5.ROS2 function package
  • 6.ROS2 node
  • 7.ROS2 topic communication
  • 8.ROS2 service communication
  • 9.ROS2 action communication
  • 10.ROS2 custom interface message
  • 11.ROS2 parameter service case
  • 12.ROS2 meta-function package
  • 13.ROS2 distributed communication
  • 14.ROS2 DDS
  • 15.ROS2 time related API
  • 16.ROS2 common command tools
  • 17.ROS2 rviz2 use
  • 18.ROS2 rqt toolbox
  • 19.ROS2 Launch startup file configuration
  • 20.ROS2 recording and playback tool
  • 21.ROS2 URDF model
  • 22.ROS2 Gazebo simulation platform
  • 23.ROS2 TF2 coordinate transformation
Download
  • Code
  • Software_tools
  • SystemFile
Download ZIP

Welcome to RDK X5 MagicBox repository

3. Voice Interaction

Voice Interaction

Repository Address

  • Voice stream processing code: https://github.com/D-Robotics/magicbox_audio_io
  • Large language model code: https://github.com/D-Robotics/magicbox_qwen_llm

Function Description

  1. This function includes an audio processing node and a voice large model node. The large model uses Qwen2.5-1.5B. ASR is based on SensorVoice. TTS and KWS are based on the Sherpa-onnx framework.
  2. In addition to the default continuous dialogue mode, it also supports keyword wake-up mode, namely "one wake-up one dialogue". Users can wake up by saying "Hello, Digua" and then have a round of dialogue, or directly have a dialogue by saying "Hello, Digua + your question.". After detecting "Hello, Digua", the light will blink. It can be switched via continuous_wake_mode in audio_io.launch.py.
  3. In addition to the default voice dialogue function, it also supports voice control. However, this function will add a lot of extra prompts, and the function loading time is longer. For configuration, refer to enable_function_call in qwen_llm.launch.py. After starting, you can use commands such as "Raise right hand" , "Raise right hand to the highest“ , "Stand up" , "Sit down" .
  4. Due to the long initialization time of the voice processing node, this node starts automatically after boot. The button only controls the start and stop of the large language model node, but the two nodes will wait for each other to start before working.
  5. Functional architecture diagram: Functional Architecture Diagram
Gesture Interaction
Network configuration

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