RDK X5 Quickstart Guide for Openclaw

An essential onboarding guide for the RDK X5 platform that leads developers from hardware setup to running real-time AI object detection.

katherineedwards2475
v1.0.0
Mar 9, 2026
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Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install rdk-x5-quickstart

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install rdk-x5-quickstart using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is RDK X5 Quickstart Guide?

The rdk-x5-quickstart skill is a foundational resource for developers entering the D-Robotics ecosystem. It provides a structured path for setting up the RDK X5 hardware, ensuring that users can successfully flash the RDK OS, manage initial boot sequences, and establish network connectivity. By utilizing Openclaw Skills, this guide simplifies the transition from raw hardware to a functional AI development environment.

Beyond basic setup, the skill validates hardware performance by running pre-configured AI models. It introduces users to both simple Python-based inference and sophisticated ROS2-based workflows using TogetherROS (TROS). This ensures that even beginners can achieve immediate results with computer vision and machine learning tasks.

RDK X5 Quickstart Guide Use Cases

  • Initial unboxing and first-time configuration of the RDK X5 developer kit.
  • Flashing official RDK OS images to microSD cards for system deployment.
  • Establishing remote access via SSH over Ethernet or WiFi networks.
  • Verifying hardware functionality using the built-in YOLOv5 object detection samples.
  • Preparing the environment for more advanced Openclaw Skills like camera management or ROS2 development.

How RDK X5 Quickstart Guide Works

  1. The process begins with downloading the official RDK OS and flashing it to a microSD card using tools like balenaEtcher or terminal commands.
  2. Upon the first boot, the system initializes and provides access via default credentials for root or sunrise users.
  3. Network connectivity is established using standard Linux network management tools to ensure package repository access.
  4. The skill guides the user through a system update to ensure all drivers and AI runtimes are current.
  5. Finally, the user executes a sample AI application, either via a Python script for quick testing or via TROS for a full real-time web-streamed detection experience.

RDK X5 Quickstart Guide Setup

To flash the image to your SD card from a Linux environment, identify your device and run:

sudo dd if=rdk_os_image.img of=/dev/sdX bs=4M status=progress && sync

Once booted, connect to your local network using nmcli:

sudo nmcli device wifi connect "YOUR_WIFI_NAME" password "YOUR_PASSWORD"

Finally, ensure your package lists are up to date to support additional Openclaw Skills:

sudo apt update && sudo apt upgrade -y

RDK X5 Quickstart Guide Data Schema & Taxonomy

The rdk-x5-quickstart skill utilizes specific system paths and metadata for its operations:

Data Type Location / Source Purpose
System Image developer.d-robotics.cc Official OS source for RDK X5.
Credentials root/root or sunrise/sunrise Default access for initial configuration.
AI Models /app/pydev_demo/07_yolov5_sample Pre-installed YOLOv5 models for validation.
Environment /opt/tros/humble/setup.bash ROS2 Humble environment configuration.
System Info rdkos_info Command to retrieve hardware and OS metadata.

RDK X5 Quickstart Guide Advanced Features

  • Support for real-time web visualization at http://:8000 for AI inference results.
  • Integration with TogetherROS (TROS) for advanced robotics and sensor fusion workflows.
  • Seamless transition paths to other Openclaw Skills for GPIO control, camera tuning, and system monitoring.
  • Compatibility with both MIPI and USB camera interfaces for flexible AI input sources.

SKILL.md


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