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Autori principali: Choi, Joonwon, Pant, Kartik Anand, Nune, Karthik, Hwang, Inseok
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2603.08633
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author Choi, Joonwon
Pant, Kartik Anand
Nune, Karthik
Hwang, Inseok
author_facet Choi, Joonwon
Pant, Kartik Anand
Nune, Karthik
Hwang, Inseok
contents We propose a reachability-based framework for reliable LLM-guided human-autonomy teaming (HAT) using signal temporal logic (STL). In the proposed framework, LLM is leveraged as a translator that transfers natural language commands given by a human operator into corresponding STL specifications or vice versa. An STL feasibility filter (SFF) is proposed to check the feasibility of the generated STL. The SFF first decomposes the complex and nested LLM translation into a set of simpler subformulas for parallelization and informative feedback generation. The reachability analysis method is then applied to verify if each subformula is feasible for a target dynamical system: if feasible, perform mission planning, otherwise, reject it. The proposed SFF can identify infeasible subformulas, more than simply providing the boolean verification results for the whole STL, thereby facilitating the feedback generation of LLM to request modification of the command to the human. Consequently, the proposed framework can allow more reliable HAT by enabling safe and informative communication between the human operator and the autonomous agent. Our experiments demonstrate that the proposed framework can successfully filter out infeasible subformulas and generate informative feedback based on such information.
format Preprint
id arxiv_https___arxiv_org_abs_2603_08633
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Reachability-based Temporal Logic Verification for Reliable LLM-guided Human-Autonomy Teaming
Choi, Joonwon
Pant, Kartik Anand
Nune, Karthik
Hwang, Inseok
Systems and Control
We propose a reachability-based framework for reliable LLM-guided human-autonomy teaming (HAT) using signal temporal logic (STL). In the proposed framework, LLM is leveraged as a translator that transfers natural language commands given by a human operator into corresponding STL specifications or vice versa. An STL feasibility filter (SFF) is proposed to check the feasibility of the generated STL. The SFF first decomposes the complex and nested LLM translation into a set of simpler subformulas for parallelization and informative feedback generation. The reachability analysis method is then applied to verify if each subformula is feasible for a target dynamical system: if feasible, perform mission planning, otherwise, reject it. The proposed SFF can identify infeasible subformulas, more than simply providing the boolean verification results for the whole STL, thereby facilitating the feedback generation of LLM to request modification of the command to the human. Consequently, the proposed framework can allow more reliable HAT by enabling safe and informative communication between the human operator and the autonomous agent. Our experiments demonstrate that the proposed framework can successfully filter out infeasible subformulas and generate informative feedback based on such information.
title Reachability-based Temporal Logic Verification for Reliable LLM-guided Human-Autonomy Teaming
topic Systems and Control
url https://arxiv.org/abs/2603.08633