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Muto RS Robot📖
01.Introduction to Muto Robot
  • 1.Accessories introduction
  • 2.Precautions for battery
  • 3.FAQ
  • 4.MutoRS Study Guide
  • 5.Quick Start Guide
02.Assembly and write system
  • 1.Raspberry Pi write system
  • 2.Assembly video
03.Remote control course
  • 1.Open and Close APP Control Program
  • 2.Mobile APP Remote Control
  • 3.USB Wireless Controller Remote Control
  • 4.Web Host Computer Remote Control
04.Remote login operation
  • 1.SSH and VNC remote login
  • 2.Jupyter Lab login and running example code
05.AI Large Model Basicsnew
  • 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
06.AI Large Model Developmentnew
  • 1.Register a model service provider account
  • 2.Configure API-KEY
  • 3.Introduction to Dify
  • 4.Dify Basic function
  • 5.AI large model development - Chatbot
  • 6.Deploy the RAG knowledge base
  • 7.RAG knowledge base + Chatbot
  • 8.AI agent workflow
  • 9.Custom wake-up response
  • 10.Core module testing tools
07.AI Large Model (Text Version)new
  • 0.MutoRS Model Setup & Details
  • 1.Semantic Understanding, Instruction Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding + Depth Camera Distance Q&A
  • 4.Multimodal Visual Understanding + Visual Line Following
  • 5.Multimodal Visual Understanding + Visual Following
  • 6.Multimodal Visual Understanding + SLAM Navigation
  • 7.Multimodal Visual Understanding + SLAM Navigation + Visual Line Following
  • 8.Intention Estimation + Multimodal Visual Understanding + SLAM Navigation + Visual Functions
08.AI Large Model (Voice Version)new
  • 0.MutoRS Model Setup & Details
  • 1.Semantic Understanding, Instruction Following
  • 2.Multimodal Visual Understanding
  • 3.Multimodal Visual Understanding + Depth Camera Distance Q&A
  • 4.Multimodal Visual Understanding + Visual Line Following
  • 5.Multimodal Visual Understanding + Visual Following
  • 6.Multimodal Visual Understanding + SLAM Navigation
  • 7.Multimodal Visual Understanding + SLAM Navigation + Visual Line Following
  • 8.Intention Estimation + Multimodal Visual Understanding + SLAM Navigation + Visual Functions
09.AI Large Model (Fun Applications)new
  • 1.Versatile performer
  • 2.Action Imitation
  • 3.Problem Solving Expert
  • 4.Exploring Unfamiliar Environments
10.Robot basic course
  • 1)Control buzzer
  • 2)Control PWM servo
  • 3)Control bus servo
  • 4)Robot forward and backward
  • 5)Robot move left and right
  • 6)Robot rotate left and right
  • 7)Control height
  • 8)Control head
  • 9)Action group performance
  • 10)Read data
  • 11)Host computer control
  • 12)Camera driver
11.Voice control coursenew
  • 1.Control Muto motion
  • 2.Control Muto tracking
  • 3.Control Muto color recognition
  • 4.Control Muto color tracking
  • 5.Control multi-point navigation
12.AI vision course
  • 0)Color HSV Calibration
  • 1)Color recognition
  • 2)Color following
  • 3)Color recognition action group
  • 4)Face detection
  • 5)QR code recognition
  • 6)QR code instructions
  • 7)Visual line following
  • 8)Motion learning
  • 9)Synchronous action teaching
13.Mediapipe course
  • 1)Hand detection
  • 2)Attitude detection
  • 3)Overall inspection
  • 4)Face detection
  • 5)Face recognition
  • 6)Face effects
  • 7)Face detection
  • 8)3D object recognition
  • 9)Brush
  • 10)Finger control
  • 11)Gesture recognition
14.Depth camera course
  • 1)Depth camera use
  • 2)Internal reference calibration
  • 3)Web page real-time monitoring
  • 4)ROS+opencv application
  • 5)QR code creation and recognition
  • 6)AR vision
  • 7)Tracking
  • 8)Obstacle recognition
  • 9)Color tracking
  • 10)KCF object tracking
  • 11)RTAB-Map 3D mapping navigation
15.Lidar course
  • 1)About lidar
  • 2)Lidar obstacle avoidance
  • 3)Lidar tracking
  • 4)Lidar guard
  • 5)Patrol
  • 6)SLAM overview
  • 7)ROS2_Gmapping mapping algorithm
  • 8)ROS2_Cartographer mapping algorithm
  • 9)About ROS2 Navigation
  • 10)ROS2 navigation and avoid
  • 11) APP mapping
  • 12)APP navigation
16.Road network navigationnew
  • 1.Road network planning and navigation environment deployment
  • 2.Constructing pose maps
  • 3.Road network annotation
  • 4.Inter-road network planning and navigation
  • 5.Road network navigation under arbitrary poses
  • 6.Path replanning
17.Multi-machine control course
  • 1)Multi-vehicle control
  • 2)Multi-vehicle navigation
18.Robot chassis control
  • 1)Hexapod gait and kinematics
  • 2)Robot information release
  • 3)Robot control
  • 4)URDF model
19.Raspberry Pi course
  • 1)Python usage
  • 2)Use APT to install Python packages
  • 3)Python virtual environment
  • 4)GPIO Zero
  • 5)Pin output high and low levels
  • 6)Pin reads high and low levels
  • 7)Pin output PWM
  • 8)Serial communication
  • 9)I2C communication
20.OpenCV course
  • 1)Introduction to Open Source CV
  • 2)Image reading and display
  • 3)Picture writing
  • 4)Image Quality
  • 5)Pixel operations
  • 6)Image zoom
  • 7)Picture cut
  • 8)Picture pan
  • 9)Picture mirroring
  • 10)Affine transformation
  • 11)Picture rotation
  • 12)perspective transformation
  • 13)Grayscale processing
  • 14)Binary image
  • 15)Edge green detection
  • 16)Line segment drawing
  • 17)Rectangular circle drawing
  • 18)Text and picture drawing
21.Docker course
  • 1)Overview and installation
  • 2)Common commands
  • 3)Deeply understand and publish images
  • 4)Hardware interaction and data processing
  • 5)Enter docker container
  • 6)Robot development environment construction
  • 7)Update docker images
22.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
23.Linux basic 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)Driver library and communication
  • 10)Static IP and hotspot mode
  • 11)Bind device ID
  • 12)Capacity expansion and resource allocation
  • 13)Back up system image
  • 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
24.Mainboard Large Model Course
Offline large model (Text Interaction)
  • 0. AI large model image description
  • 1. Deployment of large AI model environments
  • 2. Installation of 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. Llava Visual Multimodal Large Model
  • 10. MiniCPM-V Visual Multimodal Large Model
  • 11. Multimodal Visual Understanding Applications
  • 12. Multimodal Text-Based Image Application
  • 13. Multimodal Video Analysis Application
  • 14. Multimodal visual positioning applications
  • 15. Multimodal table scanning application
  • 16. Multimodal Autonomous Agent Application
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 and voice interaction
  • 5. Multimodal Text-Based Image Application
  • 6. Multimodal Video Analysis Application
  • 7. Multimodal visual positioning applications
  • 8. Multimodal table scanning application
  • 9. Multimodal Autonomous Agent Applications
  • 10. AI large model offline voice assistant
Online large model (text interaction)
  • 1.OpenRouter Large Model API Aggregation Platform
  • 2. Multimodal Visual Understanding Applications
  • 3. Multimodal visual positioning applications
  • 4. Multimodal table scanning application
  • 5. Multimodal Autonomous Agent Applications
Online large model (voice interaction)
  • 0. Voice Interaction Hardware Connection (Must Read)
  • 1. Online speech-to-text (ASR)
  • 2. Online Text-to-Speech (TTS)
  • 3. AI large model voice interaction
  • 4. Multimodal visual and voice interaction
  • 5. Multimodal visual positioning applications
  • 6. Multimodal table scanning application
  • 7. Multimodal Autonomous Agent Applications
  • 8. AI large model online voice assistant
Download
  • RemoteCtrl_APP(iOS/Android)
  • Mapping_APP(iOS_Android)
  • SystemFile_For_RPi5
  • SystemFile_Jetson
  • SystemFile_RPi
  • Code
  • VM File
  • Hardware Info
  • Instruction Manual
  • Jetson_Boot_USB.tar.gz
  • ROS2_Basic_VM
Download ZIP

Welcome to Muto RS Robot repository

4.MutoRS Study Guide

Muto-RS Tutorial Learning Path Recommendations

The recommended learning path will vary depending on the user. If you want to quickly experience the core functions of Muto-RS and see results quickly, we recommend following the "Function Experience-Oriented Learning Path" below. If you want to systematically learn the core technologies of Muto-RS and gain a deep understanding of its working principles, you can follow the "Solid Foundation-Oriented Learning Path" below.

The two learning paths only differ in the learning order; you don't need to worry about missing any important content.

In the following content, operations mentioned as running in the /root path require entering the Docker environment; those in the /home/pi path are run on the host machine (i.e., the Raspberry Pi system).

I. Function Experience-Oriented Learning Path

This path is suitable for users who want to quickly experience the core functions of Muto-RS and see results quickly.

Phase 1: Quick Start

Hardware Preparation and Basic Operations

  • Chapter 01: Introduction to Muto Robot (Quick overview)

  • Chapter 02: Assembly and write system (This part is pre-installed at the factory and can be skipped)

  • Chapter 03: Remote control course (Experience various preset control methods)

  • Chapter 04: Remote login operation (Must-read, master the use of JupyterLab and methods for connecting SSH and VNC)

    • Using SSH requires understanding some basic Linux commands, such as ls, cd, etc. (See the Linux basics section in 06. Quick Start Guide)

  • Docker related content (See the Docker section in 06. Quick Start Guide)

  • Quick start section for ROS2 related content (See the ROS2 section in 06. Quick Start Guide)

Phase 2: Basic Functions

Basic Motion Control

  • Chapter 10: Robot basic course

    • Directly learn core functions such as motion control and action performance

Phase 3: Advanced MutoRS Functions

【Depth Camera】 Visual Function Experience

  • Chapter 12: AI vision course (Basic vision functions, can also be achieved with a regular camera)
  • Chapter 13: Mediapipe course (Basic vision functions, can also be achieved with a regular camera)
  • Chapter 14: Depth camera course (Combining depth camera features)

【Lidar】 Mapping and Navigation Function Experience

  • Chapter 15: Lidar course (Focus on learning obstacle avoidance, mapping, and navigation)
  • Chapter 16: Road network navigation (Experience the cutting-edge new features of ROS2 Kilted's road_server)

【Voice Module】 Voice Control Integration

  • Chapter 11: Voice control course

    • Combining the previously learned motion, vision, and navigation functions with the voice control module

Phase 4: Embodied Intelligence

Embodied Intelligence Combined with Robot Functions

  • Chapter 06: 06. AI Large Model Development

    • The focus is on registering an account with a model service provider and setting up the environment according to the first and second sections of this chapter.
    • The remaining chapters can be skipped, and then you can directly refer to Chapter 07's [0. MutoRS Model Setup & Details]

  • Chapter 07: AI Large Model (Text Version)

  • Chapter 08: AI Large Model (Voice Version)

  • Chapter 09: AI Large Model (Fun Applications)

Phase 5: In-depth Learning of Fundamental Knowledge

In-depth learning of theory-oriented knowledge as needed

  • Choose to learn as needed:

    • ROS2 Development (Chapter 22)
    • Docker Containerization (Chapter 21)
    • Multi-machine Collaboration (Chapter 17)

II. Solid Foundation-Oriented Learning Path

This path is suitable for users who want to systematically learn ROS2 robot development, AI technology, Docker, and other core technologies through the MutoRS system, progressing from theoretical parts to advanced topics in a step-by-step manner.

Phase 1: Fundamentals

Robot Cognition and Hardware Preparation

  • Chapter 01: Introduction to the Hexapod Robot

    • Understand the robot's hardware components, version configuration, and battery usage precautions.
    • Prerequisites: None

  • Chapter 02: Assembly and write system

    • Learn robot assembly and Raspberry Pi system flashing.
    • Prerequisites: Basic hardware operation skills

Basic Operation and Remote Control

  • Chapter 03: Remote control course

    • Master remote control methods such as mobile APP, USB gamepad, and web-based control panel.
    • Prerequisites: Chapters 01-02

  • Chapter 04: Remote login operation

    • Learn SSH, VNC, and JupyterLab remote login methods.
    • Prerequisites: Chapter [02. Assembly and write system], and some basic Linux commands

  • Chapter 21: Docker

  • Master container technology, environment setup, and image management.

  • Prerequisites: Chapters [23. Linux basic course], Chapters [22. ROS2 basic course]

  • Note: Many subsequent ROS2 functions will require operation within a Docker container.

  • Chapter 22: ROS2 basic course

  • Systematically learn ROS2 architecture, node communication, tool usage, etc.

  • Prerequisites: Chapters [23. Linux basic course], Chapters [19. Raspberry Pi course], C++/Python basics

  • Chapter 18: .Robot chassis control

  • In-depth study of hexapod gait, kinematic solving, and URDF modeling.

  • Prerequisites: Chapters [22. ROS2 basic course], Chapters [10. Robot basic course]

Phase 2: Programming Fundamentals

Linux and Python Basics

  • Chapter 23: Linux basic course

    • Master basic Linux commands, file system, process management, etc.
    • Prerequisites: Completion of Chapter [04. Remote login operation]

  • Chapter 19: Raspberry Pi course

    • Learn Python environment setup, GPIO control, serial communication, etc.
    • Prerequisites: Chapters [23. Linux basic course] and basic Python syntax

Robot Basic Control

  • Chapter 10: Robot Basic Control
  • Mastering basic functions such as servo control, motion control, and data reading.
  • Prerequisites: Chapters [19. Raspberry Pi course] and Python basics

Phase 3: Vision and Perception Technology

Computer Vision Fundamentals

  • Chapter 20: OpenCV course

    • Master basic image processing, feature detection, and object recognition.
    • Prerequisites: Chapters [19. Raspberry Pi course], Python basics

  • Chapter 12: AI Vision Applications

  • Learn applications such as color recognition, face detection, and visual line following.

  • Prerequisites: Chapter [20. OpenCV course]

Advanced Computer Vision Techniques

  • Chapter 13: Mediapipe course

    • Master hand detection, pose estimation, and face recognition.
    • Prerequisites: Chapter [12. AI vision course], Chapter [20. OpenCV course]

  • Chapter 14: Depth Camera Series Courses

    • Learn how to use depth cameras (requires a basic understanding of ROS2), AR vision, etc.
    • Prerequisites: Chapter [12. AI vision course], Chapter [20. OpenCV course]

Phase 4: Lidar and Navigation

Lidar and SLAM Mapping and Navigation

  • Chapter 15: Lidar course

    • Master lidar usage, obstacle avoidance, SLAM mapping, and navigation.
    • Prerequisites: Chapter [23. Linux basic course], basic Linux operations

  • Chapter 16: Road network navigation

    • Learn road network planning, pose mapping, and path replanning.
    • Prerequisites: Chapter [15. Lidar course]

Phase 5: Advanced Development Techniques

  • Chapter 17: Multi-machine control course

    • Learn advanced functions such as multi-robot control and collaborative navigation.
    • Prerequisites: Chapter [22. ROS2 basic course]

  • Chapter 11: Voice Control Series Courses

    • Implement functions such as voice-controlled movement, line following, and navigation.
    • Prerequisites: Chapter [10. Robot basic course], Chapter [12. AI vision course], Chapter [16. Road network navigation]

Phase 6: Comprehensive Applications

  • Chapter 24: Mainboard Large Model Course

  • Chapter 05: AI Large Model Basics

    • Learn about the principles of AI large models, RAG retrieval augmentation, and embodied intelligence architecture.
    • Prerequisites: None, but programming experience is recommended.

  • Chapter 06: AI Large Model Development

    • Learn about using the Dify platform, RAG knowledge base deployment, and intelligent agent development.
    • Prerequisites: Chapter 05

  • Chapter 07: AI Large Model (Text Version)

  • Chapter 08: AI Large Model (Voice Version)

  • Chapter 09: AI Large Model (Fun Applications)

    • Prerequisites: Chapters 05-06

 

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