EgoExo++：结合按需外中心视觉与2.5D地面估计的水下ROV交互式遥操作
EgoExo++: Integrating On-demand Exocentric Visuals with 2.5D Ground Surface Estimation for Interactive Teleoperation of Underwater ROVs
AI总结：
针对水下ROV遥操作视野受限问题，提出EgoExo++方法，通过几何驱动的视觉SLAM合成外中心视图并实时估计2.5D地面，提升操作性能和用户体验。
摘要：
水下ROV（遥控潜水器）对于海底探索和任务执行不可或缺，但基于自我中心（第一人称）视频流的典型遥操作引擎限制了人类操作员的视野，并限制了在复杂、非结构化水下环境中的精确操控。为解决这一问题，我们首先提出EgoExo，一种集成到视觉SLAM流水线中的几何驱动解决方案，从自我中心摄像头馈送中按需合成外中心（第三人称）视图。我们进一步提出EgoExo++，它超越2D外中心视图合成（EgoExo），实时增强分段平面2.5D地面估计。其无锚点空中视角支持地面相对推理，如间隙和基于地形的导航标记跟随。所涉及的计算是闭式的，仅依赖于自我中心视图和单目SLAM估计，这使得它可移植到现有遥操作引擎，并对不同水体特性具有鲁棒性。我们通过2自由度室内导航和6自由度水下洞穴探索在挑战性低光条件下的广泛实验验证了方法的几何精度。为评估操作优势，我们进行了两项用户研究，分别使用模拟和真实数据，每项涉及15名参与者，比较基线自我中心遥操作和EgoExo++。结果表明，系统可用性（SUS）提高，感知工作负荷（NASA-TLX）降低，客观遥操作性能显著提升，包括任务速度提高16%，路径偏差比降低5倍，碰撞事件减少（试验中2次对比5次）。此外，我们强调了EgoExo++增强视觉在支持共享自主和具身遥操作中的作用。EgoExo++的源代码包可在https://github.com/uf-robopi/EgoExo获取。
英文摘要：
Underwater ROVs (Remotely Operated Vehicles) are indispensable for subsea exploration and task execution, yet typical teleoperation engines based on egocentric (first-person) video feeds restrict human operators' field-of-view and limit precise maneuvering in complex, unstructured underwater environments. To address this, we first propose EgoExo, a geometry-driven solution integrated into a visual SLAM pipeline that synthesizes on-demand exocentric (third-person) views from egocentric camera feeds. We further propose EgoExo++, which extends beyond 2D exocentric view synthesis (EgoExo) to augment a piecewise planar 2.5D ground surface estimation on-the-fly. Its anchor-free aerial viewpoint supports ground-relative reasoning, such as clearance and terrain-based navigation marker following. The computations involved are closed-form and rely solely on egocentric views and monocular SLAM estimates, which makes it portable across existing teleoperation engines and robust to varying waterbody characteristics. We validate the geometric accuracy of our approach through extensive experiments of 2-DOF indoor navigation and 6-DOF underwater cave exploration in challenging low-light conditions. To assess operational benefits, we conduct two user studies with simulation and real-world data, each involving 15 participants, comparing baseline egocentric teleoperation and EgoExo++. Results indicate improved system usability (SUS), reduced perceived workload (NASA-TLX), and significant gains in objective teleoperation performance, including 16% faster missions, 5-fold reduction in path deviation ratio, and fewer collision events (2 vs. 5 across trials). Furthermore, we highlight the role of EgoExo++ augmented visuals in supporting shared autonomy and embodied teleoperation. The source packages for EgoExo++ are available at: https://github.com/uf-robopi/EgoExo.
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。
