Vision-guided robotic system for flexible automation based on Answer Set Programming (ASP)

Master's Degree Thesis in Computer Science (LM-18) — Artificial Intelligence, Reliable and Secure Software curriculum — University of Parma, July 2026

Abstract

This thesis proposes the design and implementation of a vision-guided robotic system for the flexible automation of complex and repetitive tasks, with a particular focus on critical scenarios in the medical-pharmaceutical sector. The project departs from traditional rigid automation paradigms by introducing a dynamic decision-making architecture based on Answer Set Programming (ASP). This logical-declarative approach allows the development of robust action plans adaptable to unforeseen environmental events, while supporting the interpretability of the decision-making process. The system is designed to provide formal explanations for the executed actions, aligning with the principles of Explainable AI (XAI) to promote transparency, safety, and reliability.