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.
When Prolog Meets Generative Models: A New Approach for Managing Knowledge and Planning in Robotic Applications / Saccon, Enrico; Tikna, Ahmet; De Martini, Davide; Lamon, Edoardo; Palopoli, Luigi; Roveri, Marco. - 118:(2024), pp. 17065-17071. ( 2024 IEEE International Conference on Robotics and Automation, ICRA 2024 Pacific Convention Plaza Yokohama (PACIFICO Yokohama), 1-1-1, Minato Mirai, Nishi-ku, jpn 13-17 May 2024) [10.1109/ICRA57147.2024.10610800].
When Prolog Meets Generative Models: A New Approach for Managing Knowledge and Planning in Robotic Applications
Enrico Saccon;Ahmet Tikna;Edoardo Lamon;Luigi Palopoli;Marco Roveri
2024-01-01
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.| File | Dimensione | Formato | |
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