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ROSMASTER A1 PRO📖
00.Configuration and Operation Guide
  • 0. Unboxing and Review
  • 1.Assembly Videos
  • 2.User Manual
  • 3.Enter Docker (For Raspberry Pi)
  • 4.A1Pro Front Wheel Servo Calibration
  • 5.USB Camera Calibration
  • 6.Depth Camera Calibration
  • 7.FAQ
  • 8.Desktop Configuration Center and Remote Control Guide
01.Chassis Control Course
  • 1.Robot Information Publishing
  • 2.Robot Handle Control
  • 3.Robot Keyboard Control
  • 4.Linear Velocity Calibration
  • 5.Angular Velocity Calibration
  • 6.Robot URDF Model
  • 7.Robot EKF State Estimation
02.Lidar Course
  • 1.Lidar Introduction and Use
  • 2.Lidar Obstacle Avoidance
  • 3.Lidar Following
  • 4.Lidar Patrol
  • 5.GMapping-SLAM Mapping
  • 6.Cartographer-SLAM Mapping
  • 7.Slam-Toolbox Mapping
  • 8.Lifelong Mode Mapping
  • 9.Navigation2 Single Point Navigation
  • 10.Navigation2 Multi Point Navigation
  • 11.Cartographer Relocalization Navigation
  • 12.Slam-Toolbox Localization Navigation
  • 13.Synchronous Mapping And Navigation
  • 14.Aruco Visual Relocalization Navigation
  • 15.Mobile App Mapping And Navigation
  • 16.AprilTag Transport
  • 17.Color Block Transport
03.USB Camera-Depth Camera Course
  • 1.USB Camera Introduction
  • 2.USB Camera Intrinsic Calibration
  • 3.Nuwa-HP60C Camera Introduction (Depth Camera Only)
  • 4.Depth Camera Distance Measurement (Depth Camera Only)
  • 5.Depth Pseudo Color Image (Depth Camera Only)
  • 6.Block Volume Calculation (Depth Camera Only)
  • 7.Edge Detection (Depth Camera Only)
  • 8.RTAB-Map SLAM Mapping (Depth Camera Only)
  • 9.RTAB-Map Navigation (Depth Camera Only)
04.Robotic Arm and 3D Space Gripping Course
  • 0.Robotic Arm Basic Usage
  • 1.Robotic Arm Kinematics
  • 2.Robotic Arm Chassis Coordination Control
  • 3.AprilTag ID Sorting
  • 4.AprilTag Height Anomaly Sorting
  • 5.AprilTag Tracking and Grasping
  • 6.Color Block Sorting
  • 7.Color Block Height Anomaly Sorting
  • 8.Color Block Tracking and Grasping
  • 9.Wood Block Shape Sorting
  • 10.KCF Tracking and Grasping Objects
  • 11.Mediapipe Gesture ID Sorting AprilTag
  • 12.Mediapipe Gesture Height Sorting AprilTag
  • 13.Desktop Tracking and Grasping AprilTag
  • 14.3D Spatial Tracking AprilTag
  • 15.Line Following Obstacle Clearing
  • 16.Transformer Model Tracking Algorithm
05.Road Network Planning and Navigation
  • 1.Introduction To Road Network Planning
  • 2.Road Network Annotation
  • 3.Planning And Navigation Between Waypoints
  • 4.Road Network Navigation In Any Pose
  • 5.Path Re-planning
06.OpenClaw Basic Course
  • 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
07.OpenClaw Interaction Method
  • 1.OpenClaw Webchat Interaction
  • 2.OpenClaw Tui Interaction
  • 3.OpenClaw Voice Dialogue Interaction
  • 4.OpenClaw WhatsApp Interaction
08.OpenClaw Development
  • 1.OpenClaw Connecting to Robot MCP Service
  • 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 Scheduled Tasks
  • 10.OpenClaw Multi-Agent Intelligent Agent
  • 11.OpenClaw Active Interaction
  • 12.OpenClaw Vector Memory
09.OpenClaw Embodied Intelligent Application
  • 1.OpenClaw Target Tracking
  • 2.OpenClaw Arm Tracking And Grasping
  • 3.OpenClaw Arm Fixed-point Placement
  • 4.OpenClaw Waste Sorting
  • 5.OpenClaw SLAM Mapping And Navigation
  • 6.OpenClaw Navigation Transport
  • 7.OpenClaw AprilTag Grasping
  • 8.OpenClaw Color Line Patrol
  • 9.OpenClaw Visual Distance Measurement
10.OpenClaw Scenario Sandbox
  • 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
  • 1.Register a Model Service Provider Aaccount
  • 2.Configuring API-KEY
  • 3.Introduction to Dify
  • 4.Basic Dify Features
  • 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
13.AI Model - Text Version
  • 1.Semantic Understand and Command Follow
  • 2.Multimodal Visual Understand
  • 3.Multimodal Visual Understand + Robotic Arm Gripping
  • 4.Multimodal Visual Understand+SLAM Navigation
  • 5.Robotic Arm Gripping+Multimodal Visual Understand+SLAM Navigation
  • 6.Intention Estimation
14.AI Model - Voice Version
  • 1.Semantic Understand and Command Follow
  • 2.Multimodal Visual Understand
  • 3. Multimodal Large Model+Robotic Arm Gripping
  • 4.Multimodal Visual Understand+SLAM Navigation
  • 5.Robotic Arm Gripping+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 Cobotic Arm
  • 13.Gesture Grabbing and Releasing Objects
  • 14.Finger Control Robotic Arm
  • 15.Medipipe Gesture Control Robotic arm Cction 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.Scene Design
  • 8.Trajectory Planning
  • 9.Collision Detection
  • 10.3D Perception Obstacle‑Avoidance
17.Multi-vehicle Course
  • 1.Multi-vehicle Control
  • 2.Multi-vehicle Navigation
  • 3.Multi-vehicle Formation
18.YOLO26 Development
  • 1.CLI Use
  • 2.Object Detection
  • 3.Instance Segmentation
  • 4.Pose Estimation
  • 5.Image Classification
  • 6.Oriented Object Detection
  • 7.YOLOv26 + DeepSORT Tracking
  • 8.Monocular Depth Estimation
19.Control Board STM32 Driver Course
  • 0.Notes (Must Read)
  • 1.About Expansion Board
  • 2.STM32 Development Environment
  • 3.Button Control
  • 4.FreeRTOS Application
  • 5.Serial Communication
  • 6.SBUS Model Aircraft Remote Control
  • 7.CAN Bus Communication
  • 8.RGB Colorful Light Bar
  • 9.Timer Interrupt to Control PWM Servo
  • 10.Control Serial Port Servos
  • 11.Nine-axis Attitude Sensor to Obtain Data
  • 12.Control Motor
  • 13.Timer Captures the Encoder Data
  • 14.1 Kinematic Analysis of Mecanum Wheel
  • 14.2 Kinematic Analysis of Ackerman
  • 14.3 Kinematic Analysis of 4WD
  • 15.PID Control Robot Movement
20.Docker Course
  • 1.Docker Introduction and Installation
  • 2.Docker Basic Commands
  • 3.Docker Submission and Multi-Terminal Access
  • 4. Docker Startup Script
  • 5.Docker-Vscode Environment Construction
21.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
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
24.Main Control Course
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
RDKX5
  • 1.Introduction to RDK X5 board
  • 2.Write system file
  • 3.Hardware interface description
  • 4.Install case and other accessories
  • 5.Network configuration
  • 6.Remote login
  • 7.Update system
  • 8.srpi-config user guide
  • 9.config. txt configuration file
  • 10.Self-startup setting
  • 11.RDK exclusive command usage
  • 12.Linux command usage
  • 13.GPIO readwrite operation
  • 14.Image classification algorithm
  • 15.Use USB camera
  • 16.Use MIPI camera
  • 17.Binocular camera depth algorithm
  • 18. Controlling RGB Cooling Fans
Download
  • SystemFile
  • Code
  • 3D_Model_File
  • Software_Tools
  • Hardware_Info
  • Introduction_Manual
  • Script_File
  • Dify AI Agent
Download ZIP

Welcome to ROSMASTER A1 PRO repository

14.3 Kinematic Analysis of 4WD

14.3 Kinematic Analysis of 4WD

14.3 Kinematic Analysis of 4WD14.3.1、Precondition14.3.2、Establish kinematic model14.3.3、Kinematic analysis

14.3.1、Precondition

This section will analyze the kinematics equation of four-wheel drive vehicle from the aspect of four-wheel drive vehicle kinematics. Due to the structural error of the real vehicle, there will be resistance, friction and other factors in the process of movement, which is more complex. For simplicity, the analysis is only limited to the four-wheel drive vehicle in the ideal state.

 

14.3.2、Establish kinematic model

The 4WD car is abstracted into the following model, where W represents the distance between the left and right motor center points; L represents the interval between the front and rear motor center points; Motors M1, M2, M3 and M4 refer to the four driving motors of the trolley; V represents the linear speed of the trolley (forward and backward speed), ω Indicates the angular speed (rotation speed) of the car.

Ideally, by controlling the linear velocity V and angular velocity ω, It is converted to control four motors to control the movement of the 4WD car.

image-20221114174200854

14.3.3、Kinematic analysis

Let V~m1~, V~m2~, V~m3~, V~m4~be the speed values of motors M1, M2, M3 and M4, that is, the rotational speed of wheels, V~x~be the linear speed of the car, V~x~be positive for forward, V~x~be negative for backward, V~z~be the angular speed of the car, V~be positive for left, V~be negative for right, A is half of the distance W between the center points of the left and right motors of the car, A=$ frac {W} {2} $, B is half of the distance L between the center points of the front and rear motors of the car, B=$ frac {L} {2} $.

When the car moves forward or backward.

V~m1~=V~x~

V~m2~=V~x~

V~m3~=V~x~

V~m4~=V~x~

 

When the trolley rotates around the geometric center point.

V~m1~=-V~z~*(A+B)

V~m2~=-V~z~*(A+B)

V~m3~=V~z~*(A+B)

V~m4~=V~z~*(A+B)

 

According to the above formula, we can get.

V~m1~=V~x~-V~z~*(A+B)

V~m2~=V~x~-V~z~*(A+B)

V~m3~=V~x~+V~z~*(A+B)

V~m4~=V~x~+V~z~*(A+B)

 

Kinematic Analysis of Ackerman
PID Control Robot Movement

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