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Seeing, Saying, Solving: An LLM-to-TL Framework for Cooperative Robots

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arxiv 2505.13376 v1 pith:LL3GJZPJ submitted 2025-05-19 cs.RO

Dan BW Choe , Sundhar Vinodh Sangeetha , Steven Emanuel , Chih-Yuan Chiu , Samuel Coogan , Shreyas Kousik This is my paper
classification cs.RO
keywords helprobothelperrobotsframeworkimpactlanguagereasoning
verification ladder T0 review T1 audit T2 compute T3 formal
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Increased robot deployment, such as in warehousing, has revealed a need for seamless collaboration among heterogeneous robot teams to resolve unforeseen conflicts. To address this challenge, we propose a novel, decentralized framework for robots to request and provide help. The framework begins with robots detecting conflicts using a Vision Language Model (VLM), then reasoning over whether help is needed. If so, it crafts and broadcasts a natural language (NL) help request using a Large Language Model (LLM). Potential helper robots reason over the request and offer help (if able), along with information about impact to their current tasks. Helper reasoning is implemented via an LLM grounded in Signal Temporal Logic (STL) using a Backus-Naur Form (BNF) grammar to guarantee syntactically valid NL-to-STL translations, which are then solved as a Mixed Integer Linear Program (MILP). Finally, the requester robot chooses a helper by reasoning over impact on the overall system. We evaluate our system via experiments considering different strategies for choosing a helper, and find that a requester robot can minimize overall time impact on the system by considering multiple help offers versus simple heuristics (e.g., selecting the nearest robot to help).

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. pacSTL: PAC-Bounded Signal Temporal Logic from Data-Driven Reachability Analysis

    cs.LO 2025-11 conditional novelty 6.0 of 10

    pacSTL composes PAC-bounded reachable sets with interval STL to compute spec-level robustness intervals that contain an unseen trajectory's robustness with probability ≥ 1−ε.

  2. Staying on Spec: Real-Time Monitoring under Uncertainty with a Maritime Case Study

    cs.RO 2026-08 conditional novelty 5.0 of 10

    A monitoring framework based on pacSTL and data-driven reachable sets, with a sim-to-real disturbance calibration, enables real-time COLREG compliance monitoring and earlier collision avoidance.

  3. BT-TL-DMPs: A Novel Robot TAMP Framework Combining Behavior Tree, Temporal Logic and Dynamical Movement Primitives

    cs.RO 2025-07 reject novelty 4.0 of 10

    A hierarchical robot planning framework that generates behavior trees from temporal logic specifications and optimizes dynamic movement primitives to satisfy spatiotemporal constraints while preserving demonstrated mo...

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