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cs.RO2026
LLM-Guided Future Hypotheses for Horizon-Aware Exploration in Multi-Step Robot Manipulation
Mohammad Khoshnazar, Andrew Melnik, Michael Beetz
Multi-step robot manipulation requires acting under uncertainty about how the scene will evolve, making exploration and policy adaptation challenging. We study whether short-horizo…
cs.RO2025
Grounding Language Models with Semantic Digital Twins for Robotic Planning
Mehreen Naeem, Andrew Melnik, Michael Beetz
We introduce a novel framework that integrates Semantic Digital Twins (SDTs) with Large Language Models (LLMs) to enable adaptive and goal-driven robotic task execution in dynamic…