外观
论文arXiv 2610.1708916 天前
超越可达性的交互导航：基准与智能体式框架
原文链接：Interactive Navigation Beyond Reachability: Benchmark and Agentic Framework（arXiv 2610.17089 · 发布日期：2026-10-12）
Interactive Navigation Beyond Reachability: Benchmark and Agentic Framework
针对需改变连通性与目标可见性的交互导航，提出MultINav-Bench和基于状态交互图的MultINav-Agent，并在该基准验证。
核心要点
- 现有具身导航通常假设可通行性和物体状态固定，难以覆盖开门、开容器等连续交互需求。
- 论文统一建模通道导致的空间连通性变化、容器导致的目标可见性变化及其顺序依赖。
- MultINav-Agent基于持久的状态条件交互图，结合语义交互感知、视觉语言模型选动作和交互后验证。
- 在MultINav-Bench上，MultINav-Agent在channel、container和mixed任务中持续优于改造基线。
验证范围与局限：验证范围为MolmoSpaces中MultINav-Bench的channel、container与mixed ObjectGoal任务。
英文摘要 (Abstract)
Existing embodied navigation tasks commonly assume that traversability and object states remain fixed during an episode. Yet reaching a goal may require opening a door to access a room and then opening a container to reveal a hidden target. We formulate interactive navigation beyond reachability, unifying channel-induced changes in spatial connectivity, container-induced changes in target visibility, and their sequential dependencies. We introduce MultINav-Bench, a 3K-episode ObjectGoal benchmark in MolmoSpaces spanning channel, container, and mixed tasks, with interaction-necessity annotations covering required and unnecessary episodes. Its data generation pipeline automates task construction across multiple task types. The evaluation protocol separately measures navigation success, interaction effectiveness, and cost. We further propose MultINav-Agent, a three-stage agentic framework built on a persistent, state-conditioned interaction graph. Semantic interactive perception grounds entities and interaction states; a vision-language model selects task-relevant actions based on expected changes in connectivity and target observability; and post-interaction verification updates the graph to guide subsequent navigation, exploration, or interaction. Experiments on MultINav-Bench show that MultINav-Agent consistently outperforms adapted baselines across channel, container, and mixed tasks.
作者：Delun Li, Xueyao Wei, Rui Chen, Yifei Wang, Junzhi Yu, Wenjie Song, Xingyu Chen
来源
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