LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems

Artem Lykov; Maria Dronova; Nikolay Naglov; Mikhail Litvinov; Sergei Satsevich; Artem Bazhenov; Vladimir Berman; Aleksei Shcherbak; Dzmitry Tsetserukou

arXiv · 2312.09348

LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems

Artem Lykov·Maria Dronova·Nikolay Naglov·Mikhail Litvinov·Sergei Satsevich·Artem Bazhenov·Vladimir Berman·Aleksei Shcherbak·Dzmitry Tsetserukou

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Abstract

This paper introduces LLM-MARS, first technology that utilizes a Large Language Model based Artificial Intelligence for Multi-Agent Robot Systems. LLM-MARS enables dynamic dialogues between humans and robots, allowing the latter to generate behavior based on operator commands and provide informative answers to questions about their actions. LLM-MARS is built on a transformer-based Large Language Model, fine-tuned from the Falcon 7B model. We employ a multimodal approach using LoRa adapters for different tasks. The first LoRa adapter was developed by fine-tuning the base model on examples of Behavior Trees and their corresponding commands. The second LoRa adapter was developed by fine-tuning on question-answering examples. Practical trials on a multi-agent system of two robots within the Eurobot 2023 game rules demonstrate promising results. The robots achieve an average task execution accuracy of 79.28% in compound commands. With commands containing up to two tasks accuracy exceeded 90%. Evaluation confirms the system's answers on operators questions exhibit high accuracy, relevance, and informativeness. LLM-MARS and similar multi-agent robotic systems hold significant potential to revolutionize logistics, enabling autonomous exploration missions and advancing Industry 5.0.

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Artem Lykov, Maria Dronova, Nikolay Naglov, Mikhail Litvinov, Sergei Satsevich, Artem Bazhenov, Vladimir Berman, Aleksei Shcherbak, Dzmitry Tsetserukou. 2023-12-14. LLM-MARS: Large Language Model for Behavior Tree Generation and NLP-enhanced Dialogue in Multi-Agent Robot Systems. https://arxiv.org/abs/2312.09348

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