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UniTeam: Open Vocabulary Mobile Manipulation Challenge
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This report introduces our UniTeam agent - an improved baseline for the "HomeRobot: Open Vocabulary Mobile Manipulation" challenge. The challenge poses problems of navigation in unfamiliar environments, manipulation of novel objects, and recognition of open-vocabulary object classes. This challenge aims to facilitate cross-cutting research in embodied AI using recent advances in machine learning, computer vision, natural language, and robotics. In this work, we conducted an exhaustive evaluation of the provided baseline agent; identified deficiencies in perception, navigation, and manipulation skills; and improved the baseline agent's performance. Notably, enhancements were made in perception - minimizing misclassifications; navigation - preventing infinite loop commitments; picking - addressing failures due to changing object visibility; and placing - ensuring accurate positioning for successful object placement.
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Cited by 1 Pith paper
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UniLM-Nav: A Unified Framework for Zero-Shot Last-Mile Navigation
A zero-shot MLLM framework decomposes last-mile navigation into view selection, affordance grounding, and base-pose reasoning, achieving SOTA on the OVMM benchmark.
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