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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.Road network annotation

3.Road network annotation

3.Road network annotation1. Course Content2. Road network labeling2.1Start Docker2.2 Start navigation node2.3Start the ros2_kilted docker container2.4 Start road network labeling nodes2.5 Add Waypoints2.5 Add edge3. Save road network description file4.Loading and modifying road network descriptions4.1Load the road network description file4.2Editing the road network

1. Course Content

1.Use the route_tool tool to annotate and describe the .geojson format file of the road network.

2. Road network labeling

2.1Start Docker

  • Start the terminal of Humble version of Docker
start_muto_humble

image-20260106094029840

 

2.2 Start navigation node

  • When marking the road network, we need to know the exact location of the vehicle's navigation system on the map. Therefore, we first need to start the navigation node on Humble's Docker container. The location of the vehicle's navigation system on the map can be determined by its position in the base_link coordinate system.
xxxxxxxxxx
ros2 launch yahboomcar_nav navigation_slam_toolbox_launch.py map:=/root/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_nav/maps/road_map

[!NOTE]

Startup parameter description

  • map The name of the raster map to be loaded; here, the map saved in the previous lesson (road_map) is selected.

 

2.3Start the ros2_kilted docker container

  • Start the ros2_kilted container (it only needs to be started once and does not need to be started repeatedly).
xxxxxxxxxx
pi@raspberrypi:~ $ ./kilted_docker_start.sh
Found yahboom workspace, mounting...
Found code_ws directory, mounting...
Launching container...
Container started: 819a6a99aaab
Entering container...
------------------------------------
ROS_DOMAIN_ID: 38
my_robot_type: Muto | my_lidar: a1
------------------------------------
root@raspberrypi:~#

 

2.4 Start road network labeling nodes

  • Start in the terminal inside the ros2_kilted container
xxxxxxxxxx
ros2 launch road_net_route route_tool.launch.py yaml_filename:=/root/yahboomcar_ros2_ws/yahboomcar_ws/src/yahboomcar_nav/maps/road_map.yaml
  • The **yaml_filename** parameter is the path to the raster map file containing the road network to be annotated. This uses the map built in the previous lesson.
  • rviz will display the map and two coordinate systems: map is the map coordinate system, and base_link is the coordinate system of the projection point of the vehicle's chassis center onto the ground.

For easier display, we disable unnecessary TF functions in rviz, only keeping base_link.

image-20260104194502375

 

2.5 Add Waypoints

  • Click the Publish Point tool in the RViz toolbar to enter waypoint selection mode.

image-20251119154746850

 

  • Then, left-click the small blue dot at the center of the base_link coordinate system. The position field in the Route Tool tab at the bottom left will automatically be filled with the coordinates of the current point. Then click "Create" to create a waypoint.

image-20260104194638436

image-20260104194753571

  • Next, we move the vehicle's infotainment system to the next location where a waypoint needs to be marked. In this demonstration, we simply move the infotainment system to the next location where a waypoint needs to be marked.

[!TIP]

Here, the mobile robot can be controlled via keyboard, gamepad, or 2D Goal Pose navigation in RViz. It can even be directly moved to the next location that needs marking, as a pose map allows for quick and accurate global positioning of the robot.

 

  • As we can see, the global localization was lost because the vehicle's infotainment system was moved directly, and the laser contour and map environmental features no longer match. Here, we can use the pose map in conjunction with the 2D Pose Estimate tool for rapid relocalization.

image-20260104194935915

  • The vehicle's location will then be restored to its accurate position on the global map immediately.

[!TIP]

  • The fast relocalization principle here utilizes pure localization from slam_toolbox and pose map for fast scan-map matching.
  • Note: If a discrepancy is observed between the laser outline and map environment features during subsequent waypoint marking (due to cumulative errors in the odometer, wheel slippage, human movement, or other factors causing local positioning errors), this method can be used to quickly restore the vehicle's accurate positioning.
  • Repeat the above steps until all waypoints that need to be marked are completed (mark waypoints according to the user's actual needs).
  • After marking, you can turn off the left-side TF and LaserScan to check waypoints.

image-20260104195041439

2.5 Add edge

  • Select Edge in the Route Tool tab.

image-20260104195114787

 

  • Enter the starting path point of the edge in Start Node ID and the ending path point of the edge in End Node ID, then click Create to create an edge between the path points.

[!IMPORTANT]

Attention!!!

A road network is a topological structure composed of points and edges. Edges have directions. Here, creating an edge from 1 to 0 is unidirectional. If a bidirectional edge is needed, an edge from 0 to 1 must also be created.

  • Repeat the above steps to create all edges (whether to create unidirectional or bidirectional edges depends on the specific needs of the scenario).

image-20260104195219368

 

3. Save road network description file

  • In the Route Tool tab, click "save". In the pop-up window, select the path to save the file. Here, choose the same path as the map file.
  • Then, enter the file name in the "File name" field. It's recommended to keep the same name as the raster map for easy identification. The file extension must be .geojson. Finally, click "save" to save the road network description file.

image-20260104195426345

  • The terminal will print a notification message after successful saving.

image-20260104195522155

  • We can then find the road_map.geojson road network description file that we just saved on the host machine. The file contains a JSON format description of waypoints and edge information.

image-20251119171821642

 

4.Loading and modifying road network descriptions

Here we will use another saved road network annotation file and map as an example.

4.1Load the road network description file

  • If you need to modify the previous road network description file later, such as adding, removing, or editing points and edges, you can load the previous road network description file for editing.
  • Start in the terminal inside the ros2_kilted container
xxxxxxxxxx
ros2 launch road_net_route route_tool.launch.py yaml_filename:=map.yaml
  • The yaml_filename parameter is the path to the raster map file containing the road network to be annotated.

In the Route Tool tab, click Load, then select the road network description file you want to edit, and click open to load it.

image-20251119174818105

image-20251119175057600

 

4.2Editing the road network

  • To add new waypoints and edges, follow the same steps as before.
  • Click Edit to edit existing waypoints or edges.

image-20251119175320402

  • Clicking Remove allows you to edit existing waypoints or edges.

image-20251119175754294

Constructing pose maps
Inter-road network planning and navigation

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