发表机构
Fujitsu Research（富士通研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出拓扑优先的主动重建框架，解耦3DGS高保真渲染与导航，利用TSDF/占据栅格支架和Voronoi路线图，在飞行时间预算内实现安全可返回基地的室内探索重建，性能优于或媲美现有基线。
AI 中文摘要
微型飞行器（MAV）能够实现快速的室内3D重建，用于检查和时效性关键的情境感知，但必须在严格的飞行时间预算和安全约束下运行，这些约束要求具备带有保守裕度的明确返回基地（RTH）可行性。我们提出了一种拓扑优先的主动重建框架，将高保真渲染与导航解耦。一个密集的3D高斯泼溅（3DGS）地图被优化为重建目标，而一个轻量级的截断符号距离场（TSDF）/占据栅格支架支持保守的碰撞检测和在线构建稀疏的3D Voronoi骨架路线图。由于在噪声和不完整的在线融合下，直接从TSDF几何中提取路线图可能不稳定，我们使用雕刻的自由空间一致性和密集可见性检查来验证节点和边，这抑制了墙后幻影结构并稳定了规划。视点使用飞行时间预算感知的目标函数和轻量级的滚动时域前瞻在路线图上选择，以改善非短视的探索行为。我们在逼真的室内模拟基准（ReplicaCAD、Gibson和HM3D）上进行了评估，报告了重建覆盖率/误差、RTH成功率和计算成本。结果表明，在相同的飞行时间预算下，相对于最近的基于GS的基线，性能有所提升或具有竞争力。
英文摘要
Micro aerial vehicles (MAVs) enable rapid indoor 3D reconstruction for inspection and time-critical situational awareness, but must operate under strict flight-time budgets and safety constraints that require explicit return-to-home (RTH) feasibility with a conservative margin. We present a topology-first active reconstruction framework that decouples high-fidelity rendering from navigation. A dense 3D Gaussian Splatting (3DGS) map is optimized as the reconstruction target, while a lightweight Truncated Signed Distance Field (TSDF)/occupancy scaffold supports conservative collision checking and online construction of a sparse 3D Voronoi skeleton roadmap. Since directly extracting roadmaps from TSDF geometry can be unstable under noisy and incomplete online fusion, we validate nodes and edges using carved free-space consistency and dense visibility checks, which suppress behind-wall phantom structure and stabilize planning. Viewpoints are selected on the roadmap using a flight-time-budget-aware objective and a lightweight receding-horizon lookahead to improve non-myopic exploration behavior. We evaluate on photorealistic indoor simulation benchmarks (ReplicaCAD, Gibson, and HM3D), reporting reconstruction coverage/error, RTH success, and computational cost. Results demonstrate improved or competitive performance relative to recent GS-based baselines under identical flight-time budgets.
CommentsIEEE/RSJ International Conference on INTELLIGENT ROBOTS & SYSTEMS 2026
