跨异构环境的面向交互的空中移动性基准测试
Benchmarking Interaction-Oriented Aerial Mobility across Heterogeneous Environments
AI总结：
本研究提出CrossFly基准，用于评估智能体跨异构环境的面向交互的空中移动性，实验发现室内↔室外设置更具挑战性，最高成功率达9.7%，可推进空中具身智能发展。
摘要：
空中移动操作要求无人机（UAV）穿越室内、室外等异构环境，并在同一轨迹中连接导航与后续物理交互。现有空中基准通常局限于单一环境设置，限制了对智能体在连续环境过渡中的评估；当评估交互时，智能体常被初始化在目标附近，导航到交互的过渡过程基本未被评估。本研究提出CrossFly，一个用于跨异构环境的长时程面向交互的空中移动性基准。CrossFly在统一的仿真与评估框架下，包含超过20个重建场景中的1.5万条轨迹，覆盖室内、室外及室内↔室外轨迹。它进一步引入交互就绪率（IRR），用于评估终端导航状态是否为下游交互提供合适条件，且不依赖特定操作策略。对5个代表性空中视觉-语言-动作（VLA）智能体及提出的CrossFly-Agent开展实验，结果显示室内↔室外设置比单一环境设置更具挑战性，在未见场景上最高成功率达9.7%。下游操作案例研究进一步验证了面向交互的到达对后续物理交互的相关性。我们希望CrossFly助力推进空中具身智能，实现异构环境中统一的移动性与物理交互。
英文摘要：
Aerial mobile manipulation requires unmanned aerial vehicles (UAVs) to traverse heterogeneous environments such as indoor and outdoor domains, and connect navigation with subsequent physical interaction within the same trajectories. Existing aerial benchmarks are typically confined to single-environment settings, limiting evaluation of agents across continuous environmental transitions. When interaction is evaluated, agents are often initialized near the target, leaving the transition from navigation to interaction largely unassessed. This work introduces CrossFly, a benchmark for long-horizon interaction-oriented aerial mobility across heterogeneous environments. CrossFly contains 15K trajectories across more than 20 reconstructed scenes under a unified simulation and evaluation framework, covering Indoor, Outdoor, and Indoor$\leftrightarrow$Outdoor trajectories. It further introduces Interaction Readiness Rate (IRR) to assess whether terminal navigation states provide suitable conditions for downstream interaction without assuming a specific manipulation policy. Experiments with five representative aerial vision-language-action (VLA) agents and the proposed CrossFly-Agent show that Indoor$\leftrightarrow$Outdoor settings are more challenging than single-environment settings, with the highest success rate reaching 9.7% on unseen scenes. A downstream manipulation case study further validates the relevance of interaction-oriented arrival to subsequent physical interaction. We hope CrossFly helps advance aerial embodied intelligence toward unified mobility and physical interaction in heterogeneous environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
