When Prolog Meets Generative Models: a New Approach for Managing Knowledge and Planning in Robotic Applications

Enrico Saccon, Ahmet Tikna, Davide De Martini, Edoardo Lamon, Luigi Palopoli, Marco Roveri

Abstract: In this paper, we propose a robot oriented knowledge representation system based on the use of the Prolog language. Our framework hinges on a special organisation of Knowledge Base (KB) that enables: 1) its efficient population from natural language texts using semi-automated procedures based on Large Language Models (LLMs); 2) the seamless generation of temporal parallel plans for multi-robot systems through a sequence of transformations; 3) the automated translation of the plan into an executable formalism. The framework is supported by a set of open source tools and its functionality is shown with a realistic application.