OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Drones

2026-09-21

AI Summary

OpenFlyScan系统通过集成质量模型、重采计划和移动应用，解决消费级无人机大规模城市资产构建中高成本和延迟反馈问题。

Abstract

3D Gaussian Splatting (3DGS) provides high-fidelity scenes for large-scale embodied simulation, but constructing large-scale urban assets remains constrained by expensive equipment and delayed quality feedback. Preset surveys can leave complex surfaces insufficiently observed, with defects discovered only after reconstruction, requiring return visits and repeated processing. We present OpenFlyScan, a quality-guided aerial reconstruction system for consumer drones that integrates a GS quality model, a reacquisition planner, and a custom-designed mobile app. The model learns from GS rendering errors to predict regional reconstruction quality. Based on these predictions, the planner then generates complementary reacquisition strips to be executed through the app, which also supports automated oblique surveys and data transfer without additional hardware on board. Across real aerial scenes, the model effectively identifies regions that are likely to be poorly reconstructed. In the Expo West field experiment, targeted reacquisition improves PSNR at additional views by 10.95 dB. With consumer drones, OpenFlyScan integrates capture, targeted reacquisition, and reconstruction to support rapid, low-cost urban asset creation. Code and models will be made publicly available at https://openflyscan.github.io/.

Problem

• 3D Gaussian Splatting
• large-scale urban assets
• quality feedback
• reconstruction

Innovation

• 3D Gaussian Splatting
• Quality-Guided Reconstruction
• Reacquisition Planner
• Consumer Drones