In this paper, we propose a robot oriented knowledge management system based on the use of the Prolog language. Our framework hinges on a special organisation of knowledge base that enables: 1. its efficient population from natural language texts using semi-automated procedures based on Large Language Models, 2. the bumpless 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 behaviour trees). The framework is supported by a set of open source tools and is shown on a realistic application.
@article{arxiv.2309.15049,
title = {When Prolog meets generative models: a new approach for managing knowledge and planning in robotic applications},
author = {Enrico Saccon and Ahmet Tikna and Davide De Martini and Edoardo Lamon and Marco Roveri and Luigi Palopoli},
journal= {arXiv preprint arXiv:2309.15049},
year = {2023}
}