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ROSMASTER M3 PRO📖
0.Configuration and Operation Guide
  • 1. Quick start handle to control the car
  • 2. Log in to the car and view the code
  • 3. Robotic Arm Calibration
  • 4. Enter the Docker (Jetson-Nano and Raspberry Pi 5 users, see here)
  • 5. Assembly video
  • 6. Modify the firmware parameters of the car control board
  • 7. Frequently Asked Questions and Precautions
  • 8. Precautions for DIY Robotic Arm
1.Chassis Control Course
  • 1.ROS control
  • 2.Handle control
  • 3.Keyboard control
  • 4.Angular velocity calibration
  • 5.Line velocity calibration
  • 6.Line patrol automatic driving
  • 7.Patrol
2.Lidar Course
  • 1.Lidar introduction and use
  • 2.Dual Lidar fusion
  • 3.Lidar obstacle avoidance
  • 4.Lidar tracking
  • 5.Lidar guard
  • 6.Gmapping-SLAM mapping
  • 7.Cartographer-SLAM mapping
  • 8.slam_toolbox mapping
  • 9.Navigation2 single-point navigation avoid
  • 10.Navigation2 multi-point navigation avoid
  • 11.Repositioning navigation
  • 12.RTAB-Map mapping
  • 13.RTAB-Map navigation
  • 14.APP mapping navigation
  • 15.Machine code handling
  • 16.Color block transport
  • 17.Navigation via Pose-Constrained Visual Relocalizationnew
3.Depth Camera Course
  • 1.Dabai_DCW2 camera introduction
  • 2.Depth pseudo-color image
  • 3.Depth camera distance measurement
  • 4.Wood block volume measurement
  • 5.Mediapipe gesture recognition
  • 6.Edge detection
  • 7.YOLOv8 object detection
  • 8.Deep learning object tracking
  • 9. Transformer Model Tracking Algorithmnew
4.Robotic Arm and 3D Space Gripping Course
  • 1.Robotic arm solution
  • 2.Robotic arm chassis linkage control
  • 3.Machine code ID sorting
  • 4.Sorting height abnormality machine code
  • 5.Tracking and gripping machine code
  • 6.Color block color sorting
  • 7.Sorting height abnormality color block
  • 8.Tracking and gripping color block
  • 9.Wood block shape sorting
  • 10.KCF tracking and gripping objects
  • 11.Medipipe gesture ID sorting machine code
  • 12.Mediapipe gesture height sorting machine code
  • 13.Desktop tracking and gripping machine code
  • 14.3D tracking machine code
  • 15.Line patrol and obstacle removal
5.Road network planning and navigationnew
  • 1. Introduction To Road Network Planning
  • 2. Build A Pose Map
  • 3. Road Network Annotation
  • 4. Planning And Navigation Between Waypoints
  • 5. Road Network Navigation In Any Pose
  • 6. Path Re-planning
6.OpenClaw Basic Coursenew
  • 1. Introduction to OpenClaw
  • 2. OpenClaw Core Concepts
  • 3. OpenClaw API-KEY Configuration
  • 4. OpenClaw Switch Models
  • 5. OpenClaw System Prompt Words
  • 6. OpenClaw Common CLI Commands
7.OpenClaw Interaction Methodnew
  • 1. OpenClaw Webchat Interaction
  • 2. OpenClaw Tui Interaction
  • 3. OpenClaw Voice Dialogue Interaction
  • 4. OpenClaw WhatsApp Interaction
8.OpenClaw Developmentnew
  • 1. OpenClaw connects to the MCP interface of the robot
  • 2. Robot CLI Command Tool
  • 3. Robot control plugin tool
  • 4. Reply bridge plugin tool
  • 5. OpenClaw multimodal vision
  • 6. OpenClaw chassis control
  • 7. OpenClaw robotic arm control
  • 8. OpenClaw skills development
  • 9. OpenClaw timed tasks
  • 10. OpenClaw multi-agent intelligent agent
  • 11. OpenClaw active interaction
  • 12. OpenClaw vector memory
9.OpenClaw Embodied intelligent applicationnew
  • 1. OpenClaw target tracking
  • 2. OpenClaw robotic arm tracking and grasping
  • 3. OpenClaw robotic arm fixed-point placement
  • 4. OpenClaw garbage sorting
  • 5. OpenClaw slam mapping and navigation
  • 6. OpenClaw navigation transfer
  • 7. OpenClaw machine code clip
  • 8. OpenClaw color line patrol
  • 9. OpenClaw visual distance measurement
10.OpenClaw scenario sandboxnew
  • 1. Map description and prop placement
  • 2. Build sand table map
  • 3. Visual relocation markers
  • 4. Map mapping markers
  • 5. OpenClaw scenario sandbox comprehensive case
11.AI Model Basics
  • 1.AI large model types and principles
  • 2.RAG retrieval enhancement and model training samples
  • 3.Embodied intelligent robot system architecture
  • 4.Embodied intelligent functions core source code
12.AI Model Development
  • 01.Register a model service provider account
  • 02. Configuring API-KEY
  • 03. Introduction to Dify
  • 04. Basic Dify Features
  • 05. AI Large Model Development - chatbot
  • 06. Deploy the RAG knowledge base
  • 07. RAG knowledge base + chatbot
  • 08. AI agent workflow
  • 09. Custom wake-up response
  • 10. Core module testing tools
13.AI Large Model (Text Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
14.AI Large Model(Voice Version)
  • 1.Semantic understand instruction following
  • 2.Multimodal visual understand
  • 3.Multimodal visual understand+robotic arm grab
  • 4.Multimodal visual understand+SLAM navigation
  • 5.Robotic arm grab+Multimodal visual understand+SLAM navigation
  • 6.Intention estimation
15.Mediapipe Visual Course
  • 1.Hand detection
  • 2.Posture detection
  • 3.Overall detection
  • 4.Facial Landmark Detection
  • 5.Face detection
  • 6.Face special effects
  • 7.3D object recognition
  • 8.Brush
  • 9.Finger control
  • 10.Palm target positioning
  • 11.Fingertip trajectory recognition
  • 12.Fingertip gesture control robotic arm
  • 13.Gesture grabbing and releasing objects
  • 14.Finger control robotic arm
  • 15.Medipipe gesture control robotic arm action group
16.MoveIt2 Simulation Course
  • 1.MovelT2 configuration
  • 2.MovelT2 simulation-reality linkage
  • 3.Random movement
  • 4.Forward kinematics design
  • 5.Inverse kinematics design
  • 6.Cartesian path
  • 7.Trajectory planning
  • 8.Collision detection
  • 9.Scene design
17.Multi-vehicle Course
  • 1.Multi-vehicle chassis control
  • 2.Multi-vehicle robotic arm control
  • 3.Multi-vehicle navigation
  • 4.Multi-vehicle formation
18.Control Board Course
  • 1.Development environment setup
  • 2.Control board STM32 basic routine
  • 3.Control board micro_ros basic routine
19.Docker Course
  • 1、Docker overview and docker installation
  • 2、Common commands for docker image containers
  • 3、Docker images deeply understand and publish images
  • 4、Docker hardware interaction and data processing
  • 5、Enter the bot's docker container
  • 6、Robot development environment construction in Docker
20.Image Processing Basics Course
  • 1. Introduction to Open Source CV
  • 2. Image reading and display
  • 3. Image writing
  • 4. Image quality
  • 5. Pixel Operation
  • 6. Image zoom
  • 7. Image cutting
  • 8. Image translation
  • 9. Image Mirroring
  • 10. Affine Transformation
  • 11. Image Rotation
  • 12. Perspective Transformation
  • 13. Grayscale processing
  • 14. Image Binarization
  • 15. Edge Detection
  • 16. Line drawing
  • 17. Rectangle and circle drawing
  • 18. Drawing text and pictures
21.Main Control Course
Jetson Nano B01
  • 1. Introduction to the Jetson Nano B01 SUB Board
  • 2. Burn the system image
  • 3. Re-read the memory card or USB drive that has been burned
  • 4. Startup system
  • 5. Jetson Nano B01 System and Desktop Introduction
  • 6. Memory card or USB flash drive expansion
  • 7. Network Configuration
  • 8. SSH remote login & file transfer
  • 9. VNC Remote Login
  • 10. Jetson Nano B01 system backup
  • 11. Jetson Nano Swap space increased
  • 12. Installation and use of Jtop
Jetson Orin Nano_NX
  • 1.Jetson Orin board introduction
  • 2.Restore the factory image system
  • 3.Backup SSD system
  • 4.SSD expansion
  • 5.Network configuration
  • 6.SSH remote login
  • 7.VNC remote control
  • 8.Remote file transfer
  • 9.Jtop tool
  • 10.Exchange space expansion
Raspberry Pi
  • 1. Introduction to Raspberry PI 5
  • 2. Raspberry PI system installation and backup
  • 3. Powering the Raspberry PI 5
  • 4. Startup of Raspberry PI 5
  • 5. Update and upgrade operating system
  • 6. Introduction to raspi-config tool
  • 7. config.txt file description
  • 8. Network Configuration
  • 9. remote access
  • 10. Transfer files remotely
  • 11. Set display resolution and rotation
  • 12. Set screen to sleep
  • 13. Play audio and video
  • 14. Using USB camera
  • 15. Using MIPI camera
  • 16. Get real-time temperature of Raspberry Pi
22.Linux System Course
  • 1.Introduction to Linux system
  • 2.Ubuntu file system
  • 3.Ubuntu common commands
  • 4.Ubuntu common editors
  • 5.Ubuntu software operation commands
  • 6.Virtual machine installation
  • 7.SSH remote control
  • 8.VNC remote control
  • 9.Transfer files remotely
  • 10.Driver library and communication
  • 11.Static IP and hotspot mode
  • 12.Bind device ID
  • 13.Capacity expansion and resource allocation
  • 14.Update system software sources
  • 15.Set root user password
  • 16.sudo free password
  • 17.Connect to WiFi network
  • 18.View system version
  • 19.Customized service management
  • 20.Back up system image
23.ROS2 Basic Course
  • 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
  • Mapping_APP(iOS_Android)
  • Robot_Image_System_File
  • Code-Firmware
  • Instruction_Manual
  • VM_File
  • Software_Tools
  • Firmware_DriverFile
  • 3D_Model_File
  • ROS2_Basic_VM
  • Other_Annex
Download ZIP

Welcome to ROSMASTER M3 PRO repository

10. OpenClaw multi-agent intelligent agent

OpenClaw Multi-Agent Intelligent Agents

OpenClaw Multi-Agent Intelligent Agents1. Course ContentCourse OverviewLearning Objectives2. Creating Agents2.1 Creating Agents Using the CLI Wizard2.2 Agent Directory Structure2.4 Configuring Bindings2.5 Restarting the Gateway to Apply Configuration3. Editing Agent Prompts3.2 Editing Steps3.3 Configuration Example: Creating a Customer Support Bot Agent4. Deleting Agents4.1 Deleting via CLI Commands4.2 Manually Cleaning Up Agent Directories4.3 Cleaning Up Binding Configurations

1. Course Content

Course Overview

  • OpenClaw's multi-agent intelligent agent feature allows multiple isolated agents to run within the same gateway. Each agent has its own independent workspace, state directory, and session history.
  • The multi-agent architecture is suitable for scenarios with multiple roles, such as one agent responsible for programming development and another for social media operations, with data isolation and no interference between them.

Learning Objectives

  1. Understand the concept and applicable scenarios of OpenClaw multi-agent intelligent agents.
  2. Master the creation of new agents using CLI commands.
  3. Master the methods for editing agent prompt files (AGENTS.md / SOUL.md / IDENTITY.md, etc.).
  4. Master the operation of deleting an agent.

2. Creating Agents

OpenClaw runs one agent by default (agentId is main). Additional isolated agents can be created using the following methods.

2.1 Creating Agents Using the CLI Wizard

OpenClaw provides the openclaw agents add command, which utilizes an interactive wizard to quickly create new agents:

openclaw agents add <agentId>

For example, to create a "work" agent named work:

xxxxxxxxxx
openclaw agents add work

image-20260430171444829

image-20260430171505534

Upon execution, OpenClaw automatically performs the following actions:

  1. Creates the agent directory: ~/.openclaw/agents/<agentId>/
  2. Creates the workspace bootstrap files: including AGENTS.md, SOUL.md, IDENTITY.md, TOOLS.md, USER.md, etc.

2.2 Agent Directory Structure

Once an agent is created, a complete file structure is generated within the ~/.openclaw/agents/<agentId>/ directory:

xxxxxxxxxx
~/.openclaw/agents/<agentId>/
├── agent/
│   ├── auth-profiles.json    # Authentication profiles
│   ├── config.json           # Agent configuration
│   └── ...
└── sessions/                 # Session history storage
    └── <SessionId>.jsonl

The agent's workspace files are located within their respective workspace directories, where you can edit the bootstrap files to define the agent's behavior and personality. ### 2.3 Verifying Agent Creation

Once creation is complete, you can view all agents and their binding statuses using the following command:

xxxxxxxxxx
openclaw agents list --bindings

image-20260430171641638

2.4 Configuring Bindings

A Binding is a rule that routes messages from a channel account to a specific agent. Each binding consists of:

  • agentId: The ID of the target agent.
  • match: The matching rule (based on channel, peer account, etc.).

Example Configuration (openclaw.json):

xxxxxxxxxx
{
  "agents": {
    "list": [
      { "id": "main", "workspace": "~/.openclaw/workspace" },
      { "id": "work", "workspace": "~/.openclaw/workspace-work" }
    ]
  },
  "bindings": [
    {
      "agentId": "main",
      "match": { "channel": "whatsapp", "peer": { "kind": "direct", "id": "+15551230001" } }
    },
    {
      "agentId": "work",
      "match": { "channel": "whatsapp", "peer": { "kind": "direct", "id": "+15551230002" } }
    }
  ]
}

2.5 Restarting the Gateway to Apply Configuration

After creating agents or modifying binding configurations, you must restart the Gateway:

xxxxxxxxxx
openclaw gateway restart

After restarting, verify the status of the agents and channels:

xxxxxxxxxx
openclaw agents list --bindings
openclaw channels status --probe

3. Editing Agent Prompts

Each agent's personality, behavioral rules, and capabilities are defined through Bootstrap Files located within its workspace. By editing these files, you can customize the agent's prompts. ### 3.1 Introduction to Bootstrap Files

In the first turn of a new session, OpenClaw injects the following workspace files into the agent's context:

FilePurpose
AGENTS.mdOperational instructions and memory; defines the behavioral rules the agent must follow.
SOUL.mdPersona, boundaries, and tone; defines the agent's personality traits.
IDENTITY.mdAgent name, vibe, and emoji identifier.
TOOLS.mdUser-maintained instructions and conventions for tool usage.
USER.mdUser profile and preferred forms of address.
BOOTSTRAP.mdOne-time initial setup ritual (can be deleted once completed).

3.2 Editing Steps

Step 1: Navigate to the Agent's Workspace Directory

xxxxxxxxxx
# Custom Agent Workspace (if a specific workspace was specified during creation)
cd ~/.openclaw/workspace-<agentId>

Step 2: Edit SOUL.md to Define the Agent's Personality

​x
# Role Setting
You are a professional programming assistant, specializing in Python and ROS2 development.
​
# Tone and Style
Maintain a professional and concise tone; respond in Chinese.
​
# Behavioral Boundaries
- Do not perform dangerous operations.
- Do not delete important user files.

Step 3: Edit AGENTS.md to Set Operational Instructions

xxxxxxxxxx
# Operational Rules
- When answering questions, prioritize using the MCP Tool to retrieve the latest information.
- If you encounter uncertain information, proactively ask the user for confirmation.
- Before executing an action, first outline the steps you are about to perform.

Step 4: Edit IDENTITY.md to Define the Agent's Identity

xxxxxxxxxx
# Name
Code Assistant
​
# Emoji
🤖
​
# Bio
I am your dedicated programming assistant, ready to help you complete ROS2 development and Python programming tasks!

Step 5: Restart the Gateway to Apply Changes

xxxxxxxxxx
openclaw gateway restart

[!TIP]

  • The content of the bootstrap file is injected into the LLM context during the very first turn of a new session; therefore, you must start a new session to see the effects of any modifications.
  • You can initiate a new session within the WebChat interface using the /new command.
  • Empty files will be skipped and will not be injected into the context.
  • If a file is missing, OpenClaw will inject a placeholder line indicating "Missing File."

3.3 Configuration Example: Creating a Customer Support Bot Agent

xxxxxxxxxx
# SOUL.md
# Role Definition
You are a friendly customer support bot responsible for answering user inquiries regarding robot products.
​
# Tone and Style
Enthusiastic, patient, and professional; respond in Chinese.
​
# Behavioral Boundaries
- Do not disclose internal system configuration information.
- Do not perform operations that compromise the security of the bot.
xxxxxxxxxx
# AGENTS.md
# Operational Guidelines
- For product-related functional issues, first use `SeeWhat` to observe the current environment.
- For technical issues, guide users to consult relevant tutorial documentation.
- For questions that cannot be answered, record the query and escalate it to technical personnel.

4. Deleting Agents

4.1 Deleting via CLI Commands

To delete an agent that is no longer needed, use the following command:

xxxxxxxxxx
openclaw agents delete <agentId>

For example, to delete an agent named work:

xxxxxxxxxx
openclaw agents delete work

image-20260430172010258

4.2 Manually Cleaning Up Agent Directories

After executing the CLI command, it is recommended to also clean up the following residual data:

xxxxxxxxxx
# Delete the agent's data directory
rm -rf ~/.openclaw/agents/<agentId>
​
# Delete the agent's workspace
rm -rf ~/.openclaw/workspace-<agentId>

4.3 Cleaning Up Binding Configurations

After deleting an agent, you must also remove the corresponding binding records and agent list entries from the openclaw.json configuration file:

  1. Open the configuration file: ~/.openclaw/openclaw.json
  2. Remove the entry for the specific agent from agents.list.
  3. Remove any binding rules related to that agent from bindings.
  4. Save the file, then restart the gateway:
xxxxxxxxxx
openclaw gateway restart

[!WARNING]

  • Deleting an agent will permanently remove that agent's session history, authentication configurations, and all associated data.
  • Before proceeding with the deletion, please ensure that you have backed up any important data.
  • If the agent is currently running, it is recommended to first disable any associated channel bindings before performing the deletion.
OpenClaw timed tasks
OpenClaw active interaction

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