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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

3. Meta AI Llama 3.2 model

Llama 3.2

Llama 3.21. Model Size2. Performance3. Using Llama 3.23.1 Running Llama 3.23.2 Starting a Conversation3.3 Ending a Conversation3.4 Chinese ConversationReferences

Meta Llama 3.2 is a series of advanced open-source large-scale language models (LLMs) developed by the Meta AI department.

1. Model Size

ModelSize
llama3.2:1b1.3GB
llama3.2:3b2.0GB

The Raspberry Pi 5 2GB version can only run models with 1B parameters.

The Raspberry Pi 5 1GB version can't run this case,Please refer to the online large model case.

2. Performance

Llama 3.2 instruction-tuned benchmarks

3. Using Llama 3.2

3.1 Running Llama 3.2

Use the run command to start running the model. If the model is not already downloaded, it will automatically pull the model from the Olama model library:

ollama run llama3.2:3b

image-20250627184454105

3.2 Starting a Conversation

xxxxxxxxxx
How many minutes are there in a day?

Response time depends on your hardware configuration, so please be patient!

image-20250627185035604

3.3 Ending a Conversation

Use the Ctrl+d shortcut or /bye to end the conversation!

3.4 Chinese Conversation

If you don't have a Chinese input method, please refer to the Chinese input method switching tutorial

Chinese Conversation:

image-20250627185428020

References

Ollama

Official website:https://ollama.com/

GitHub：https://github.com/ollama/ollama

Llama 3.2

Official website:https://www.llama.com/docs/model-cards-and-prompt-formats/llama3_2/

Ollama corresponding model:https://ollama.com/library/llama3.2

Installation of large model dialogue platform
Alibaba Cloud Qwen3 Model

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