AI Goalkeeper Robot Software Development https://www.youtube.com/watch?v=n6yo1QSYZak*
Budget: $250 – $750 USD
Software Objective:
Develop an integrated system to control, train, test, and monitor a goalkeeper robot in simulated or real robotic soccer matches. The software should handle computer vision, trajectory prediction, motor control, and performance analysis.
?? Target Audience:
Robotics engineers, researchers, developers, and competition teams (e.g., RoboCup).
? Main Modules:
? Computer Vision
Capture images from USB or CSI cameras.
Ball detection using OpenCV (color, shape, or AI-based).
Ball tracking and trajectory prediction.
Field recognition (lines, goals).
? AI and Defense Logic
Prediction algorithms (e.g., Kalman filter).
Decision-making module (what move to make).
Machine learning-based training (optional).
Simulation of offensive scenarios.
? Control and Command
Interface with microcontrollers (via ROS or serial).
Send speed/position commands (PID control).
Support for DC motors/servos or omni wheels.
Real-time response with low latency.
? Monitoring and Testing
Data logging (ball position, reaction time, success/failures).
Graphical performance visualization.
Playback of previous plays for analysis.
Automated test simulation.
? Virtual Simulator (Optional)
Integration with Gazebo/Webots for hardware-free testing.
Sandbox mode to test AI strategies.
?️ Technical Requirements:
Primary Language: Python
Suggested Libraries: OpenCV, NumPy, Matplotlib, scikit-learn, ROS (Robot Operating System)
Environment: ROS Noetic + Ubuntu 20.04 or later
Compatible Hardware: Raspberry Pi, Jetson Nano, Arduino, ESP32, etc.
GUI (optional): PyQt5 or Tkinter
? Additional (Future) Features:
Multiplayer mode (with other robots).
Web interface for remote control.
Integration with extra sensors (LIDAR, ultrasonic).
Over-the-air (OTA) firmware updates.
? Mockups and Layouts:
Main interface: Camera feed + AI status + manual control panel.
Testing screen: Logs, performance charts, play replay.
Develop an integrated system to control, train, test, and monitor a goalkeeper robot in simulated or real robotic soccer matches. The software should handle computer vision, trajectory prediction, motor control, and performance analysis.
?? Target Audience:
Robotics engineers, researchers, developers, and competition teams (e.g., RoboCup).
? Main Modules:
? Computer Vision
Capture images from USB or CSI cameras.
Ball detection using OpenCV (color, shape, or AI-based).
Ball tracking and trajectory prediction.
Field recognition (lines, goals).
? AI and Defense Logic
Prediction algorithms (e.g., Kalman filter).
Decision-making module (what move to make).
Machine learning-based training (optional).
Simulation of offensive scenarios.
? Control and Command
Interface with microcontrollers (via ROS or serial).
Send speed/position commands (PID control).
Support for DC motors/servos or omni wheels.
Real-time response with low latency.
? Monitoring and Testing
Data logging (ball position, reaction time, success/failures).
Graphical performance visualization.
Playback of previous plays for analysis.
Automated test simulation.
? Virtual Simulator (Optional)
Integration with Gazebo/Webots for hardware-free testing.
Sandbox mode to test AI strategies.
?️ Technical Requirements:
Primary Language: Python
Suggested Libraries: OpenCV, NumPy, Matplotlib, scikit-learn, ROS (Robot Operating System)
Environment: ROS Noetic + Ubuntu 20.04 or later
Compatible Hardware: Raspberry Pi, Jetson Nano, Arduino, ESP32, etc.
GUI (optional): PyQt5 or Tkinter
? Additional (Future) Features:
Multiplayer mode (with other robots).
Web interface for remote control.
Integration with extra sensors (LIDAR, ultrasonic).
Over-the-air (OTA) firmware updates.
? Mockups and Layouts:
Main interface: Camera feed + AI status + manual control panel.
Testing screen: Logs, performance charts, play replay.