FC-Vision: Real-Time Visibility-Aware Replanning for Occlusion-Free Aerial Target Structure Scanning in Unknown Environments

2026-02-14

AI Summary

This work addresses the critical limitation of existing UAV-based structural scanning methods in unknown environments, where neglecting occlusion often leads to severe visibility degradation and poor reconstruction quality. To overcome this, we propose a real-time visibility-aware replanning framework that, for the first time, embeds dense surface visibility constraints directly into trajectory optimization. Our approach employs a two-layer decomposition strategy to jointly optimize coverage efficiency and occlusion avoidance, integrating occlusion-free viewpoint repair with a 5-DoF spatial segmentation technique for clean perceptual connectivity. Notably, the method is designed for non-intrusive integration into existing systems. Extensive experiments in both simulated and real-world scenarios demonstrate substantial improvements: up to a 55.32% increase in maximum coverage and a 73.17% reduction in occlusion rate, all while maintaining real-time performance.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Sampling/Simulation-based Search
• Computer Vision: Learning & Optimization for CV

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines

Abstract

Autonomous aerial scanning of target structures is crucial for practical applications, requiring online adaptation to unknown obstacles during flight. Existing methods largely emphasize collision avoidance and efficiency, but overlook occlusion-induced visibility degradation, severely compromising scanning quality. In this study, we propose FC-Vision, an on-the-fly visibility-aware replanning framework that proactively and safely prevents target occlusions while preserving the intended coverage and efficiency of the original plan. Our approach explicitly enforces dense surface-visibility constraints to regularize replanning behavior in real-time via an efficient two-level decomposition: occlusion-free viewpoint repair that maintains coverage with minimal deviation from the nominal scan intent, followed by segment-wise clean-sensing connection in 5-DoF space. A plug-in integration strategy is also presented to seamlessly interface FC-Vision with existing UAV scanning systems without architectural changes. Comprehensive simulation and real-world evaluations show that FC-Vision consistently improves scanning quality under unexpected occluders, delivering a maximum coverage gain of 55.32% and a 73.17% reduction in the occlusion ratio, while achieving real-time performance with a moderate increase in flight time. The source code will be made publicly available.

Problem

• occlusion
• visibility
• aerial scanning
• unknown environments
• target structure

Innovation

• visibility-aware replanning
• occlusion-free scanning
• real-time UAV planning
• surface visibility constraints
• plug-in integration