Applied Robotics and AI with Python

This unit brings together object-oriented and functional Python skills to build, test, and deploy robot behaviors powered by sensors and machine learning. Students will integrate trained networks, manage data and files (CSV/binary/timestamps), and use virtual environments and included vendor software to reliably run and troubleshoot Python programs on hardware while reflecting on future and ethical implications.

Learning Objectives

• Apply object-oriented and functional Python constructs (classes, methods, inheritance, anonymous functions, and custom exceptions) to design, implement, and test reusable robot control modules that operate LEDs, motors, and sensors.
• Integrate and evaluate a trained machine learning model on hardware by loading the network, running the Python Robot Interface Test and the FindAndChaseTheBall program, and documenting performance and failure modes.
• Analyze and transform data and file formats by reading/writing binary files and CSVs, converting between CSV records and Python objects/dictionaries (including multi-key dictionaries), and handling dates/times and time zones for sensor and logging data.
• Manage development and deployment workflows by creating and using virtual environments, employing included Adeept software tools, applying debugging and testing strategies, and assessing practical and ethical considerations for AI-enabled robotics.