JetRover (Jetson Nano Version)

JetRover (Jetson Nano Version)

  • 1. Quick Start Guide
    • 1.1 JetRover Version Description
    • 1.2 Hardware Installation and Power-on Preparation
      • 1.2.1 Install Depth Camera and Robot Arm
      • 1.2.2 Install Main Control Board (Applicable to the robot version without Controller)
      • 1.2.3 Install 7-inch LCD Screen
      • 1.2.4 Wiring Instructions (Key Points)
    • 1.3 Charging Instructions and Battery Usage Guide
      • 1.3.1 Charging Instructions
      • 1.3.2 Charging Operation
    • 1.4 First Power-on
      • 1.4.1 Usage Guideline
      • 1.4.2 Robot Startup State & Testing Instruction
    • 1.5 APP Control
      • 1.5.1 APP Installation
      • 1.5.2 Connection Mode Introduction
      • 1.5.3 APP Control Instruction
      • 1.5.4 Robot Control
      • 1.5.5 Lidar
      • 1.5.6 Target Tracking
      • 1.5.7 Line Following
      • 1.5.8 Gesture Control
      • 1.5.9 AR
    • 1.6 Development Environment Setup and Configuration
      • 1.6.1 Remote Connection Tool Introduction & Installation
      • 1.6.2 AP Direct Connection Mode Operations
      • 1.6.3 LAN Mode Connection
      • 1.6.4 Method to Restore WI-FI Option in Menu Bar
      • 1.6.5 USB Cable Fixed IP Connection
      • 1.6.6 System Command-line Terminal Introduction
      • 1.6.7 Robot Version Configuration Tool Instruction
      • 1.6.8 Remote Desktop Resolution Adjustment
    • 1.7 Wireless Handle Control
      • 1.7.1 Usage Guideline
      • 1.7.2 Device Connection
      • 1.7.3 Button Instructions
    • 1.8 Manual Mapping
      • 1.8.1 Preparation for Mapping
      • 1.8.2 Operation Steps
    • 1.9 Autonomous Mapping
    • 1.10 Autonomous Navigation
      • 1.10.1 ROS1 Autonomous Navigation
      • 1.10.2 ROS2 Autonomous Navigation
    • 1.11 Hardware Introduction
      • 1.11.1 Hardware System Wiring Diagram
      • 1.11.2 Electronic Control System Introduction
      • 1.11.3 Robot Controller
      • 1.11.4 Bus Servo
      • 1.11.5 Hall Encoder DC Gear Motor
      • 1.11.6 Vision Module
      • 1.11.7 Lidar
      • 1.11.8 Others
    • 1.12 ROS Usage Introduction
      • 1.12.1 ROS Main Control Hardware Connection
      • 1.12.2 ROS Serial Port Communication Instruction
    • 1.13 System Software Framework
      • 1.13.1 ROS1 Directory and Functional File Introduction
      • 1.13.2 ROS2 Directory and Functional File Introduction
    • 1.14 STM32 Source Code Instruction
      • 1.14.1 Source Code Introduction
      • 1.14.2 Control Process
      • 1.14.3 Program Framework
      • 1.14.4 Program Analysis
      • 1.14.5 Kinematics Model
      • 1.14.6 Project Compilation
      • 1.14.7 Download Program Using USB Cable
    • 1.15 Flash Image
      • 1.15.1 Preparations
      • 1.15.2 SD Card/SSD(Solid-state Drive) Formatting
      • 1.15.3 Flash Image
  • 2. Basic Development Courses
    • 2.1 Controller Hardware Course
      • 2.1.1 ROS Robot Controller Hardware Introduction
      • 2.1.2 ROS Robot Controller Schematic Explanation
    • 2.2 STM32 Development Fundamentals
      • 2.2.1 Development Environment Setup
      • 2.2.2 Light up LED
      • 2.2.3 Project Compilation & Download
      • 2.2.4 SWD Simulation Debugging
      • 2.2.5 Using a LED Blinking Program with FreeRTOS
    • 2.3 RosRobot Controller Program Analysis
  • 3. ROS1-Chassis Motion Control Lesson
    • 3.1 Kinematics Analysis
      • 3.1.1 Overview:
      • 3.1.2 Mecanum Wheel:
      • 3.1.3 Tank Chassis
    • 3.2 Motion Control
      • 3.2.1 IMU, Linear Velocity and Angular Velocity Calibration
      • 3.2.2 Publish IMU and Odometer Data
      • 3.2.3 Robot Speed Control
  • 4. ROS1-Lidar Lesson
    • 4.1 Lidar Introduction
      • 4.1.1 Preface
      • 4.1.2 Lidar Composition and Classification
      • 4.1.3 Switch Lidar Version
    • 4.2 Lidar Working and Ranging Principle
      • 4.2.1 Lidar Ranging
      • 4.2.2 Lidar Working Result
    • 4.3 Lidar Obstacle Avoidance
      • 4.3.1 Initiate Lidar Game through App
      • 4.3.2 Initiate Lidar Game Using Command
    • 4.4 Lidar Following
      • 4.4.1 Initiate Lidar Game through App
      • 4.4.2 Initiate Lidar Game Using Command
    • 4.5 Lidar Guarding
      • 4.5.1 Initiate Lidar Game through App
      • 4.5.2 Initiate Lidar Game Using Command
  • 5. ROS1-JetRover Depth Camera Basic Lesson
    • 5.1 Depth Camera Configuration
      • 5.1.1 Network Configuration
      • 5.1.2 Install Dependency
      • 5.1.3 Construct Workspace
    • 5.2 Install Depth Camera ROS SDK
    • 5.3 Usage of Depth Camera
      • 5.3.1 Enable Camera Service
      • 5.3.2 LDP Protection
    • 5.4 Camera Calibration
      • 5.4.1 Preface
      • 5.4.2 Operation Steps
    • 5.5 Data Type and Point Cloud
      • 5.5.1 Point Cloud Description
      • 5.5.2 Data Type of Point Cloud
      • 5.5.3 Point Cloud
    • 5.6 Web Real-Time Monitoring
      • 5.6.1 Access Live Camera Feed Through Web
      • 5.6.2 Enable APP Auto-Start Service
  • 6. ROS1-Mapping Navigation Lesson
    • 6.1 Mapping
      • 6.1.1 SLAM Mapping Principle
      • 6.1.2 Gmapping Mapping Algorithm
      • 6.1.3 Hector Mapping Algorithm
      • 6.1.4 Karto Mapping Algorithm
      • 6.1.5 Cartographer Mapping Algorithm
      • 6.1.6 Frontier Autonomous Mapping
      • 6.1.7 Explore_Lite Autonomous Mapping
      • 6.1.8 RRT Exploration Mapping
      • 6.1.9 ORBSLAM2 and ORBSLAM3 Mapping
      • 6.1.10 RTAB-VSLAM 3D Mapping & Navigation
      • 6.1.11 App Mapping
    • 6.2 Navigation
      • 6.2.1 ROS Robot Autonomous Navigation
      • 6.2.2 AMCL Adaptive Monte Carlo Positioning
      • 6.2.3 Local Path Planning
      • 6.2.4 Point-to-Point and Multi-Point Navigation and Obstacle Avoidance
      • 6.2.5 RTAB-VSLAM 3D Mapping & Navigation
      • 6.2.6 App Navigation
  • 7 ROS1-Multi-robot Formation Manual
    • 7.1 Muti-robot Communication Configuration
      • 7.1.1 Definition of the Master and Slave
      • 7.1.2 Preparations
      • 7.1.3 Network Connection Configuration
      • 7.1.4 Install & Import Virtual Machine
      • 7.1.5 Configure Virtual Machine
      • 7.1.6 Configure Master
      • 7.1.7 Configure Slave
      • 7.1.8 Configure Communication Between Virtual Machine and Robot
      • 7.1.9 Synchronize Time (Must-read!!)
    • 7.2 Group Control
      • 7.2.1 Preparations
      • 7.2.2 Enable Service
      • 7.2.3 Handle Buttons Function
    • 7.3 Multi-robot Mapping
      • 7.3.1 Preparation
      • 7.3.2 Map with Gmapping Algorithm
    • 7.4 Multi-robot Formation
      • 7.4.1 Preparation
      • 7.4.2 Enable Formation Service
    • 7.5 Multi-robot Navigation
      • 7.5.1 Preparation
      • 7.5.2 Enable Navigation Service
      • 7.5.3 Usage Instruction of RIVZ
    • 7.6 Multi-robot Surrounding
      • 7.6.1 Preparation
      • 7.6.2 Enable Surrounding Service
  • 8 ROS1-STM32 Controller Lesson
  • 9 ROS1-ROS+OpenCV Lesson
    • 9.1 Color Threshold Adjustment
      • 9.1.1 Open/Close LAB TOOL
      • 9.1.2 LAB TOOL Interface Layout Instruction
      • 9.1.3 Adjust Color Threshold
      • 9.1.4 Add New Color
    • 9.2 Color Recognition
      • 9.2.1 Recognition Process
      • 9.2.2 Operation Steps
      • 9.2.3 Outcome
      • 9.2.4 Program Analysis
    • 9.3 Generate & Recognize QR Code
      • 9.3.1 Generate QR Code
      • 9.3.2 QR Code Recognition
    • 9.4 AprilTag Recognition
      • 9.4.1 Program Logic
      • 9.4.2 Operation Steps
      • 9.4.3 Outcome
      • 9.4.4 Extension Function - ID Recognition
    • 9.5 AR Vision
      • 9.5.1 Program Logic
      • 9.5.2 Operation Steps
      • 9.5.3 Outcome
    • 9.6 Line Following
      • 9.6.1 File Path
      • 9.6.2 Outcome
      • 9.6.3 Program Analysis
    • 9.7 KCF Object Tracking
      • 9.7.1 KCF Introduction
      • 9.7.2 Program Logic
      • 9.7.3 Operation Steps
      • 9.7.4 Outcome
      • 9.7.5 Program Analysis
  • 10 ROS1-ROS+Machine Learning Lesson
    • 10.1 Machine Learning Fundamentals
      • 10.1.1 Machine Learning Introduction
      • 10.1.2 Machine Learning Library Introduction
    • 10.2 Machine Learning Application
      • 10.2.1 GPU Acceleration
      • 10.2.2 TensorRT Acceleration
      • 10.2.3 Yolov5 Model
      • 10.2.4 YOLOv5 Running Procedure
      • 10.2.5 Image Collecting & Labeling
      • 10.2.6 Image Labeling
      • 10.2.7 Data Format Conversion
      • 10.2.8 Model Training
      • 10.2.9 TensorRT Road Sign Detection
      • 10.2.10 Traffic Sign Model Training
      • 10.2.11 Waste Card Model Training
      • 10.2.12 Physical Model Training
    • 10.3 MediaPipe Man-Robot Interaction
      • 10.3.1 MediaPipe Introduction
      • 10.3.2 Image Background Segmentation
      • 10.3.3 3D Object Detection
      • 10.3.4 Face Detection
      • 10.3.5 3D Face Detection
      • 10.3.6 Hand Key Point Detection
      • 10.3.7 Body Key Points Detection
      • 10.3.8 Fingertip Trajectory Recognition
      • 10.3.9 Human Body Tracking
      • 10.3.10 Integration of Body Posture and RGB Control
      • 10.3.11 Pose Detection
      • 10.3.12 FAQ
    • 10.4 Autonomous Driving Debugging Lesson V1.0
      • 10.4.1 Props Setup & Notices
      • 10.4.2 Operation Steps
      • 10.4.3 Program Outcome
      • 10.4.4 Recognition & Debugging
    • 10.5 Autonomous Driving v1.0
      • 10.5.1 Lane Keeping
      • 10.5.2 Road Sign Detection
      • 10.5.3 Traffic Light Recognition
      • 10.5.4 Turning Decision Making
      • 10.5.5 Autonomous Parking
      • 10.5.6 Integrated Application
      • 10.5.7 FAQ
  • 11 ROS1-Robotic Arm Control
    • 11.1 Robotic Arm Basic Control
      • 11.1.1 Get to Know Robotic Arm
      • 11.1.4 Action Calling
      • 11.1.5 Action Editing
      • 11.1.6 Integrate Action Files
      • 11.1.7 Export and Import Action Files
    • 11.2 Robotic Arm Visual Application
      • 11.2.1 Application Overview
      • 11.2.2 Hand Tracking
      • 11.2.3 Color Recognition and Sorting
      • 11.2.4 Color Tracking
      • 11.2.5 Line-Following Obstacle Clearance
      • 11.2.6 Waste Sorting
      • 11.2.7 Fixed Point Navigation
    • 11.3 3D Vision
      • 11.3.1 Edge Detection
      • 11.3.2 Cross the Single-plank Bridge
      • 11.3.3 Object Tracking
      • 11.3.4 Callback Function:
      • 11.3.5 Run Function
      • 11.3.6 Tracking and Gripping
      • 11.3.7 Object Classification
  • 12 ROS1-MoveIt & Gazebo Simulation
    • 12.1 URDF Model Introduction V1.0
      • 12.1.1 URDF Model
      • 12.1.2 ROS Robot URDF Model Description
    • 12.2 MoveIt Simulation V1.0
      • 12.2.1 MoveIt Configuration
      • 12.2.2 MoveIt Use Notice & Control
      • 12.2.3 MoveIt Random Motion
      • 12.2.4 MoveIt Kinematics Design
      • 12.2.5 Inverse Kinematic Analysis
      • 12.2.6 Robot Arm Coordinate System Introduction
      • 12.2.7 MoveIt Cartesian Path
      • 12.2.8 MoveIt Collision Detection
      • 12.2.9 MoveIt Scenario Design
      • 12.2.10 MoveIt Trajectory Planning
    • 12.3 Gazebo Simulation V1.0
      • 12.3.1 Gazebo Introduction
      • 12.3.2 Gazebo xacro Model Visualization
      • 12.3.3 Gazebo Hardware Simulation
      • 12.3.4 Gazebo Mapping Simulation
      • 12.3.5 FAQ
      • 12.3.6 Gazebo Navigation Simulation
  • 13 ROS1-Voice Control Lesson
    • 13.1 Voice Control Basic Lesson
      • 13.1.1 R818 Noise Reduction Board
      • 13.1.2 6-Channel Circular Microphone Array
      • 13.1.3 Wiring & Serial Port Debugging
      • 13.1.4 Virtual Machine Installation and Configuration
      • 13.1.5 Replace Voice Resource Package and APPID
      • 13.1.6 Configure Microphone Port
      • 13.1.7 Wake Up Microphone Through Command
    • 13.2 Six-Microphone Circular Array Installation
    • 13.3 Voice Interaction Application
      • 13.3.1 6-Channel Microphone Array Configuration (Must Read)
      • 13.3.2 Voice-Controlled Car Movement
      • 13.3.3 Voice-Control Robotic Arm
      • 13.3.4 Voice-Controlled Color Tracking
      • 13.3.5 Voice-Controlled Color Sorting
      • 13.3.6 Voice-Controlled Waste Sorting
      • 13.3.7 Voice-Controlled Multi-Point Navigation
      • 13.3.8 Voice-Controlled Navigation transportation
    • 13.4 Switching Wake Words Between Chinese and English
  • 14 ROS Basic Course
    • 14.1 ROS1 Basic Course
    • 14.2 ROS2 Basic Course
  • 15 Docker Container Course
  • 16 ROS2-Motion Control Course
    • 16.1 Kinematics Analysis
      • 16.1.1 Overview:
      • 16.1.2 Mecanum Wheel:
      • 16.1.3 Ackermann Chassis
      • 16.1.4 Tank Chassis
    • 16.2 Motion Control
      • 16.2.1 IMU, Linear Velocity and Angular Velocity Calibration
      • 16.2.2 Publish IMU and Odometer Data
      • 16.2.3 Robot Speed Control
  • 17 ROS2-Lidar Course
    • 17.1 Lidar Introduction
      • 17.1.1 Preface
      • 17.1.2 Lidar Composition and Classification
      • 17.1.3 Switch Lidar Version
    • 17.2 Lidar Working and Ranging Principle
      • 17.2.1 Lidar Ranging
      • 17.2.2 Lidar Working Result
    • 17.3 Lidar Obstacle Avoidance
    • 17.4 Lidar Following
    • 17.5 Lidar Guarding
  • 18 ROS2-Depth Camera Basic Course
    • 18.1 Depth Camera Configuration
      • 18.1.1 Install and Configure ROS2
      • 18.1.2 Version Options
      • 18.1.3 Check Ubuntu’s Software and Update Sources
      • 18.1.4 Set Encoding Format
      • 18.1.5 Set the Download Source for ROS2
      • 18.1.6 Install ROS2
      • 18.1.7 Install Additional Dependency
      • 18.1.8 Set Environment Variables
      • 18.1.9 Test ROS2 System
      • 18.1.10 Network Configuration
      • 18.1.11 Install Dependency
    • 18.2 Construct Workspace
    • 18.3 Install Depth Camera ROS SDK
    • 18.4 Usage of Depth Camera
      • 18.4.1 Enable Camera Service
      • 18.4.2 View Image Using rqt_image_view Tool
      • 18.4.3 View Image Using rviz
      • 18.4.4 LDP Protection
    • 18.5 Data Type and Point Cloud
      • 18.5.1 Introduction to Point Cloud
      • 18.5.2 Understanding Point Cloud Data Types
      • 18.5.3 Point Cloud
  • 19 Mapping & Navigation Course
    • 19.1 Mapping
      • 19.1.1 URDF Model
      • 19.1.2 Explanation of ROS Robot URDF Model
      • 19.1.3 Principles of SLAM Map Building
      • 19.1.4 slam_toolbox Mapping Algorithm
      • 19.1.5 RTAB-VSLAM 3D Vision Mapping & Navigation
    • 19.2 Navigation Tutorial
      • 19.2.1 ROS Robot Autonomous Navigation
      • 19.2.2 AMCL Adaptive Monte Carlo Positioning
      • 19.2.3 Local Path Planning
      • 19.2.4 Point-to-Point and Multi-Point Navigation and Obstacle Avoidance
      • 19.2.5 Launch Description
      • 19.2.6 RTAB-VSLAM 3D Navigation
  • 20 ROS2-ROS+OpenCV Course
    • 20.1 Color Threshold Adjustment
      • 20.1.1 Open/Close LAB TOOL
      • 20.1.2 LAB TOOL Interface Layout Instruction
      • 20.1.3 Adjust Color Threshold
      • 20.1.4 Add New Color
    • 20.2 Color Recognition
      • 20.2.1 Recognition Process
      • 20.2.2 Operation Steps
      • 20.2.3 Program Outcome
      • 20.2.4 Program Analysis
    • 20.3 Generate & Recognize QR Code
      • 20.3.1 Generate QR Code
      • 20.3.2 QR Code Recognition
    • 20.4 Autonomous Line Following
      • 20.4.1Recognition Procedure
      • 20.4.2 Autonomous Line Following Operation
      • 20.4.3 Program Analysis
  • 21 ROS2-ROS+Machine Learning Course
    • 21.1 Autonomous Driving Debugging Lesson-v1.0
    • 21.2 Autonomous Driving v1.0
      • 21.2.1 Lane Keeping
      • 21.2.2 Road Sign Detection
      • 21.2.3 Traffic Light Recognition
      • 21.2.4 Turning Decision Making
      • 21.2.5 Autonomous Parking
      • 21.2.6 Integrated Application
      • 21.2.7 FAQ
    • 21.3 MediaPipe Man-Robot Interaction
      • 21.3.1 MediaPipe Introduction
      • 21.3.2 Image Background Segmentation
      • 21.3.3 3D Object Detection
      • 21.3.4 Face Detection
      • 21.3.5 3D Face Detection
      • 21.3.6 Hand Key Point Detection
      • 21.3.7 Body Key Points Detection
      • 21.3.8 Fingertip Trajectory Recognition
      • 21.3.9 Posture Control
      • 21.3.10 Human Body Tracking
      • 21.3.11 Integration of Body Posture and RGB Control
      • 21.3.12 Pose Detection
  • 22 ROS2-Robot Arm Control Course
    • 22.1 Robotic Arm Basic Control
    • 22.2 Robot Arm Deviation Adjustment (Optional) V1.0
      • 22.2.1 Introduction to Robot Arm
      • 22.2.2 Adjustment Steps
      • 22.2.3 FAQ
    • 22.3 Robotic Arm Visual Application
      • 22.3.1 Hand Tracking
      • 22.3.2 Color Recognition and Sorting
      • 22.3.3 Color Tracking
      • 22.3.4 Line-Following Obstacle Clearance
      • 22.3.5 Waste Sorting
      • 22.3.6 Fixed Point Navigation
    • 22.4 3D Vision
      • 22.4.1 Edge Detection
      • 22.4.2 Cross the Single-plank Bridge
      • 22.4.3 Object Tracking
      • 22.4.4 Tracking and Gripping
      • 22.4.5 Object Classification
  • 23 ROS2-MoveIt & Gazebo Simulation
    • 23.1 Virtual Machine Installation and Configuration
      • 23.1.1 Virtual Machine Installation and Import
      • 23.1.2 Configuration
    • 23.2 Introduction to URDF Models
      • 23.2.1 URDF Model
      • 23.2.2 ROS Robot URDF Model Instructions
    • 23.3 MoveIt2 Simulation
      • 23.3.1 MoveIt2 Kinematics Design
      • 23.3.2 MoveIt2 Configuration
      • 23.3.3 MoveIt2 Control
      • 23.3.4 MoveIt2 Random Movement
      • 23.3.5 MoveIt2 Cartesian Path
      • 23.3.6 MoveIt2 Collision Detection
      • 23.3.7 MoveIt2 Scene Design
      • 23.3.8 MoveIt2 Trajectory Planning
      • 23.3.9 Simulation and Robotic Arm Synchronization
    • 23.4 Gazebo Simulation
      • 23.4.1 Introduction to Gazebo
      • 23.4.2 Gazebo xacro Model Visualization
      • 23.4.3 Hardware Simulation in Gazebo
      • 23.4.4 Gazebo Mapping Simulation
      • 23.4.5 Gazebo Navigation Simulation
      • 23.4.6 Gazebo and MoveIt2 Simulation Integration
  • 24 ROS2-Voice Control Course
  • 25 AI Large Language Model Course (Overseas Version)
    • 25.1 Multi-modal Models Application
      • 25.1.1 Configure the Large Model API Key
      • 25.1.2 Version Confirmation
      • 25.1.3 Voice Control with Multimodal Models
      • 25.1.4 Autonomous Line Following with Multimodal Models
      • 25.1.5 Color Tracking with Multimodal Models
    • 25.2 Embodied AI Application
      • 25.2.1 Obtain and Configure the Large Model API Key
      • 25.2.2 Version Confirmation
      • 25.2.3 Overview of Embodied Intelligence
      • 25.2.4 Real-Time Detection in Embodied AI Applications
      • 25.2.5 Vision Tracking in Embodied AI Applications
      • 25.2.6 Smart Home Assistant in Embodied AI Applications
      • 25.2.7 Intelligent Transport in Embodied AI Applications
  • Appendix
JetRover (Jetson Nano Version)
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