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This is a Quantitative Study study.

September 29, 2025Open Access

EMMOE: A Comprehensive Benchmark for Embodied Mobile Manipulation in Open Environments

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EMMOE provides a comprehensive benchmark for performing complex robot tasks with user instructions, and evaluates agent capabilities across diverse scenarios.
The benchmark integrates high-level tasks with low-level execution metrics, improving assessment methods for mobile manipulation tasks in open environments.
We collect a dataset featuring various attributes and detailed process annotations to aid in LLM training and performance evaluation.
The performance of our agent system, utilizing decision optimization and error detection, is demonstrated across multiple models and policies.

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Proposed benchmark measures robot performance in interpreting user tasks using LLMs, suggesting improvements in outcome metrics.

Li et al. (2025) studied this question.

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