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RDK S600 Developer Kit📖
1.RDK S600 board introduction
  • 1.1 RDK S600 board introduction
  • 1.2 System Flashing
  • 1.3 Hardware Interface Description
  • 1.4 Accessory Installation
  • 1.5 Camera Expansion Board
  • 1.6 MCU Interface Expansion Board
  • 1.7 Precautions for Using the 15.6-inch Screen
  • 1.8 System Boot Modes
2.RDK S600 basic course
  • 2.1 Network Configuration
  • 2.2 Remote Login
  • 2.3 System Update
  • 2.4 Boot Auto-Start Configuration
  • 2.5 RDK Exclusive Command Usage
  • 2.6 Linux Command Usage
  • 2.7 Examples of GPIO Read and Write Operations
  • 2.8 Using the USB Camera
  • 2.9 Solid-state mounting
  • 2.10 SSD expansionnew
3.TogetheROS.Bot Vision Applications
  • 1. About TogetheROS. Bot
  • 2. System Installation
  • 3. Object Detection(YOLO)
  • 4. Image Classification(mobilenetv2)
  • 5. Image Segmentation(mobilenet_unet)
  • 6. Perception Algorithm(BEV)
  • 7. Human Detection and Tracking (Ultralytics YOLO Pose)
4. Offline AI Large Model Development
Offline large model (Text Interaction)
  • 1. AI large model environment deployment
  • 2. Install large model dialogue platform
  • 3. Meta AI Llama 3.2 model
  • 4. Alibaba Cloud Qwen3 model
  • 5. Microsoft Phi-4 mini model
  • 6. DeepSeek - DeepSeek-R1 model
  • 7. Alibaba Cloud Qwen2.5vl Visual Multimodal Large Model
  • 8. Google Gemma3 Visual Multimodal Large Model
  • 9. Lava Visual Multimodal Large Model
  • 10. MiniCPM-V Visual Multimodal Large Model
  • 11. Multimodal visual understand application
  • 12. Multimodal text image application
  • 13. Multimodal visual localization application
  • 14. Multimodal table scanning application
  • 15. Multimodal Autonomous Agent Applications
Offline large model (Voice Interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Offline speech-to-text (ASR)
  • 2. Offline Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual understanding voice interaction
  • 5. Multimodal Text-to-Image application
  • 6. Multimodal video analytics application
  • 7. Multimodal visual localization application
  • 8. Multimodal table scanning application
  • 9. Multimodal autonomous agent application
  • 10. AI Large Model Offline Voice Assistant
5. Online AI Large Model Development
Online large model (Text Interaction)
  • 1.OpenRouter large model API aggregation platform
  • 2.Multimodal visual understand application
  • 3.Multimodal visual localization application
  • 4.Multimodal table scanning application
  • 5.Multimodal autonomous proxy application
Online large model (Voice Interaction)
  • 0.Voice interaction hardware connection (ReadMe)
  • 1.Online speech to text (ASR)
  • 2.Online text to speech (TTS)
  • 3.AI large model voice interaction
  • 4.Multimodal visual understand speech interaction
  • 5.Multimodal visual localization application
  • 6.Multimodal table scanning application
  • 7.Multimodal autonomous proxy application
  • 8.AI large model online voice assistant
6.YOLO26 tutorials
  • 01.YOLO26 environment
  • 02.CLI use
  • 03.Object detection
  • 04.Instance segmentation
  • 05.Pose estimation
  • 06.Image classification
  • 07.Oriented object detection
  • 08.Model conversion
  • 09.Dataset annotation
  • 10.Model training - conversion
  • 11.Model prediction
7.OpenClaw Advanced Development
  • 1. OpenClaw Deployment
  • 2. OpenClaw and WhatsApp Plugin Application
  • 3. OpenClaw TUI Interaction
  • 4. OpenClaw WebChat Interaction
  • 5. OpenClaw Gate Gateway Operation Manual
  • 6. OpenClaw Plugin Function Introduction
  • 7. OpenClaw Tools Introduction
  • 8. OpenClaw ClawHub Introduction (skill Installation)
  • 9.OpenClaw Application - File Management
  • 10.OpenClaw Application - Browser Control
  • 11.OpenClaw Application - Camera
  • 12.OpenClaw Application - Script Execution
  • 13.OpenClaw Application - AI Programming (Peripheral & GPIO Control)
  • 14. OpenClaw Application - Dedicated AI Assistant
  • 15. OpenClaw Configure Web Search Capability
8.ROS2 basic course
  • 1.Introduction to ROS2
  • 2.ROS2 install Jazzy
  • 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
  • System_File
  • Code
  • 3D_Model_File
  • Tools_Software
Download ZIP

Welcome to RDK S600 Developer Kit repository

2. System Installation

TogetheROS.Bot Environment Setup

TogetheROS.Bot supports installation on the RDK with Ubuntu 20.04/22.04/24.04 system. Installing through DEB packages on Ubuntu system is simple and recommended for users who want to experience it initially.

1.Environment Setup

Before installing tros.b, it is recommended to upgrade the RDK system image to the latest version.

If the image has already been installed, you can upgrade it by running the commands sudo apt update and sudo apt upgrade.

Friendly Reminder:

  • If you have installed system version 1.x, you need to upgrade to version 2.x.
  • For instructions on how to check your system version number, please see FAQs.

2. Installing TogetheROS.Bot

2.1 Installing and Upgrading TogetheROS.Bot via apt

Prerequisites

  • The environment setup is complete.
  • The RDK system has been installed.
  • The RDK can access the internet normally.
  • The RDK can be accessed remotely via SSH.

Note:

  • The 2.x version of tros.b only supports 2.x system images. The 1.x version of tros.b (https://developer.d-robotics.cc/api/v1/fileData/TogetherROS/index.html) only supports 1.x systems.
  • If you are using a 1.x system image, you need to upgrade your system 1.2 apt Installation and Upgrade | RDK DOC to version 2.x.
  • For instructions on how to check your system and tros.b version numbers, please see the FAQs.
Dependencies1.x tros.b2.x tros.b
1.x System Image√x
2.x System Imagex√

Installing tros.b

Note: The RDK IP used here is 192.168.2.59. You need to replace it with your own RDK IP during installation.

Log in to RDK:

xxxxxxxxxx
ssh root@192.168.2.59

Install the tros.b package:

  • Foxy
  • Humble
  • Jazzy
xxxxxxxxxx
sudo apt update
sudo apt install tros-jazzy

Note: If you encounter the error E: Unmet dependencies. Try 'apt --fix-broken install' with no packages (or specify a solution).' after running the installation command, please execute the commandapt --fix-broken install` to install the related dependencies before installing tros.b.

After the installation is complete, check the files in the /opt directory

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ls /opt/
hobot  tros

The tros.b is installed in the /opt directory.

Upgrade tros.b

Taking RDK installation as an example, the upgrade method for x86 Ubuntu is the same as that for RDK.

Login to RDK:

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ssh root@192.168.2.59

Upgrade tros.b deb package:

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sudo apt update
sudo apt upgrade

 

Check the current tros.b version of Foxy

  • Jazzy

    Open a terminal and type apt show tros-Jazzy in the command line.

You can see that the current tros.b version has been upgraded to 2.5.4.

Note:

  • The version number Version displayed in the query is the actual version of tros.b installed. This example uses version 2.5.4.
  • For detailed release information on tros.b, please see Release History)。

2.2Install from source code

Prerequisites:

  • The development machine can access the D-Robotics organization on D-Robotics.
  • Docker is installed on the development machine.

Compiling tros.b

1 Using Dockerfiles

This part of the operation is all done on the development machine.

  • Foxy
  • Humble
  • Jazzy
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## Create a directory
cd  /mnt/data/kairui.wang/test
mkdir -p cc_ws/tros_ws/src
## Obtain the Docker for cross-compilation
wget http://archive.d-robotics.cc/TogetheROS/cross_compile_docker/pc_tros_ubuntu24.04_v1.0.1.tar.gz
## Load the Docker image
sudo docker load --input pc_tros_ubuntu24.04_v1.0.1.tar.gz 
## Check the corresponding image ID for pc_tros
sudo docker images
## Launch Docker and mount the directory
sudo docker run -it --entrypoint="/bin/bash" -v PC local directory: Docker directory imageID, here is an example using:
docker run -it --entrypoint="/bin/bash" -v /mnt/data/kairui.wang/test:/mnt/test 4cbdb9d61e19
2 Obtaining the tros.b Source Code

This part of the operation is all completed within the Docker container on the development machine.

Here, we take the /mnt/test directory in the Docker container as an example.

  • Foxy
  • Humble
  • Jazzy
xxxxxxxxxx
cd /mnt/test/cc_ws/tros_ws
## Obtain the configuration file
git clone https://github.com/D-Robotics/robot_dev_config.git -b jazzy 
## Execute cd robot_dev_config and use the "git tag --list" command to view the available release versions
## Use the "git reset --hard [tag number]" command to specify the release version. For detailed instructions, refer to the "Compile Specific Version tros.b" section on this page
## Pull the source code
vcs-import src < ./robot_dev_config/ros2_release.repos 

The directory structure of the entire project is as follows:

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├── cc_ws
│   ├── sysroot_docker
│   │   ├── etc
│   │   ├── lib -> usr/lib
│   │   ├── opt
│   │   └── usr
│   └── tros_ws
│       ├── robot_dev_config
│       └── src

 

The tros_ws/robot_dev_config path contains the configuration and script files needed for code fetching, compilation, and packaging. The tros_ws/src path stores the fetched code. The sysroot_docker path contains the header files and libraries required for cross-compilation, corresponding to the / directory of the RDK. For example, the path for the media library in sysroot_docker is sysroot_docker/usr/lib/hbmedia/, while the path in the RDK is /usr/lib/hbmedia/.

During compilation, the installation path of sysroot_docker is specified through the CMAKE_SYSROOT macro in the robot_dev_config/aarch64_toolchainfile.cmake compilation script.

3 Cross-Compilation

All of these operations are performed inside the docker on the development machine.

xxxxxxxxxx
## Compile tros.b version X3 using build.sh
bash ./robot_dev_config/build.sh -p X3
​
## Compile tros.b version RDK Ultra using build.sh.
bash ./robot_dev_config/build.sh -p Rdkultra
​
## Compile tros.b version X5 using build.sh
bash ./robot_dev_config/build.sh -p X5
​
## Compile tros.b version S100 using build.sh
bash ./robot_dev_config/build.sh -p S100
​
## Compile tros.b version S600 using build.sh
bash ./robot_dev_config/build.sh -p S600

After successful compilation, a message will prompt: N packages compiled and passed.

If using minimal_build.sh for minimal compilation, you can further compress the deployment package size by executing ./minimal_deploy.sh -d "install_path".

Install tros.b

Copy the compiled directory to the RDK and rename it as tros. Here, we place the deployment package in the /opt/tros directory to be consistent with the deb installation directory.

Compile the specified version tros.b

In the section Compile, in the step 2 Obtain the Code, the default is to fetch the latest version of tros.b source code. If you need to get a specific release version of the source code, you need to make the following modifications:

xxxxxxxxxx
## Get the configuration file
git clone https://github.com/D-Robotics/robot_dev_config.git -b develop 
cd robot_dev_config
## View available release versions
git tag --list
## Switch to the specified version number, here we take tros.b 2.0.0 as an example
git reset --hard tros_2.0.0
cd ..
## Pull code
vcs-import src < ./robot_dev_config/ros2_release.repos

3. Using ROS2 package

Prerequisite: TogetheROS.Bot installed successfully

tros.b is fully interface-compatible with ROS 2 Foxy/Humble/Jazzy versions and can reuse the extensive ROS 2 toolchains. This guide uses the installation and usage of the ROS 2 image-transport package as an example to demonstrate how to use ROS packages in tros.b.

3.1 Installing ROS2 package

3.1.1 When adding the ROS apt source s.b, the ROS apt source is automatically added, so there is no need to add it manually.

Update apt repository

xxxxxxxxxx
sudo apt update

 

3.1.2 Install packages

  • Foxy
  • Humble
  • Jazzy
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sudo apt install ros-jazzy-image-transport
sudo apt install ros-jazzy-image-transport-plugins

 

3.2Using ROS2 package

  • Foxy
  • Humble
  • Jazzy
xxxxxxxxxx
source /opt/tros/jazzy/setup.bash
ros2 run image_transport list_transports

 

The running result is as follows, showing the supported image formats by image_transport package.

​x
sunrise@ubuntu:~$ ros2 run image_transport list_transports
Declared transports:
image_transport/compressed
image_transport/compressedDepth
image_transport/raw
image_transport/theora
image_transport/zstd
​
Details:
----------
"image_transport/compressed"
 - Provided by package: compressed_image_transport
 - Publisher: 
      This plugin publishes a CompressedImage using either JPEG or PNG compression.
    
 - Subscriber: 
      This plugin decompresses a CompressedImage topic.
    
----------
"image_transport/compressedDepth"
 - Provided by package: compressed_depth_image_transport
 - Publisher: 
      This plugin publishes a compressed depth images using PNG compression.
    
 - Subscriber: 
      This plugin decodes a compressed depth images.
    
----------
"image_transport/raw"
 - Provided by package: image_transport
 - Publisher: 
      This is the default publisher. It publishes the Image as-is on the base topic.
    
 - Subscriber: 
      This is the default pass-through subscriber for topics of type sensor_msgs/Image.
    
----------
"image_transport/theora"
 - Provided by package: theora_image_transport
 - Publisher: 
      This plugin publishes a video packet stream encoded using Theora.
    
 - Subscriber: 
      This plugin decodes a video packet stream encoded using Theora.
    
----------
"image_transport/zstd"
 - Provided by package: zstd_image_transport
 - Publisher: 
      This plugin publishes a ZstdImage
    
 - Subscriber: 
      This plugin decompresses a zstdImage.
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