主动空间检查以实现有效且高效的具身探索
Active Spatial Inspection for Effective and Efficient Embodied Exploration
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中文总结 AI 辅助
针对具身探索中任务成功率与效率问题，提出空间检查引导的ACE框架，结合证据感知与暴露移动，实验显示导航成功率提升18.0%，问答效率提升10.3%。
中文摘要 AI 辅助
在具身探索中，实现高任务成功率和效率始终是核心追求。现有框架通常通过空间上粗略且间接的评估来引导智能体行为，基于提示性线索和方向，然而此类设计可能难以判断线索是否充分以及是否需要进一步检查，导致过早终止或过度持续，最终降低任务成功率和效率。本工作从空间显式的角度重新思考具身探索，并引入了空间检查引导的主动探索（ACE）框架，该框架将基于证据的感知与基于暴露信息的移动相结合，建立了一种空间分辨的决策范式。基于证据的感知通过将细粒度定位与聚焦验证相结合来增强推断有效性，将提示性线索转化为精确的决定性视觉支持。基于暴露信息的移动通过前瞻性优先级排序和回顾性抑制来促进方向判断，选择有前景的方向以实现高效的空间进展。ACE缓解了防止过早终止与避免不必要持续之间的张力。大量实验表明，ACE在导航任务成功率上比先前最先进的基线高出18.0%，在问答探索效率上高出10.3%，推进了有效且高效的具身探索。
英文摘要
Achieving high task success and efficiency remains a central pursuit in embodied exploration. Existing frameworks typically guide agent behavior through a spatially coarse and indirect assessment of suggestive cues and directions, yet such designs may struggle to judge cue sufficiency and the need for further inspection, leading to early termination or excessive continuation and ultimately reducing task success and efficiency. This work rethinks embodied exploration from a spatially explicit standpoint and introduces the spatial-inspection-guided ACtive Exploration (ACE) framework coupling evidence-grounded perception with exposure-informed movement and establishing a spatially resolved decision paradigm. Evidence-grounded perception strengthens inferential validity by integrating granular localization with focused verification, turning suggestive cues into precise decisive visual support. Exposure-informed movement promotes directional judgment through prospective prioritization and retrospective suppression, selecting promising directions for efficient spatial progress. ACE alleviates the tension between preventing early termination and avoiding unnecessary continuation. Extensive experiments demonstrate that ACE achieves 18.0% higher navigation task success and 10.3% higher exploration efficiency for question answering than prior state-of-the-art baselines, advancing effective and efficient embodied exploration.
发表机构
- The Hong Kong Polytechnic University（香港理工大学）
- China Three Gorges University（三峡大学）
- Huazhong University of Science and Technology（华中科技大学）
- Shenzhen University（深圳大学）
- Nanjing University of Aeronautics and Astronautics（南京航空航天大学）
机构由 AI 辅助整理，请以论文原文为准。
