Integrated Python Robotics and AI

This capstone unit integrates Python programming fundamentals with hands‑on robotics and applied AI to build, test, and deploy a complete robot application. Students will combine classes, file I/O, exception handling, time management, virtual environments, and a trained neural network to control sensors and actuators, evaluate system performance, and plan improvements.

Learning Objectives

• Analyze and debug Python programs that integrate classes, methods, inheritance, anonymous functions, and exception handling to identify and fix runtime and logic errors in robot applications.
• Apply file I/O, CSV and binary data handling, and datetime/time zone APIs to convert CSV data into Python objects/dictionaries, persist logs, and synchronize timed behaviors for robotic systems.
• Demonstrate the ability to assemble, configure, and run a complete Python robot project by managing virtual environments, controlling hardware (LEDs, motors, sensors), and invoking a trained neural network (e.g., FindAndChaseTheBall) to perform autonomous tasks.
• Evaluate the performance of trained models and the overall robot system using tests and logs, and propose at least two concrete improvements to enhance model accuracy, reliability, or maintainability.