两架无人机协作实现70米远距离高精度三维建图
Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline
- 双机协同用可变基线提升立体视觉感知范围
- 70米内相对误差2.3%-9.7%，深度范围提升350%
- 适合大规模未知环境下的无人机集群导航
轻量级长距离建图对大型未知环境中无人机群的安全导航至关重要。传统固定短基线立体视觉系统感知范围有限。为此，我们提出飞行协同立体（Flying Co-Stereo），一种跨智能体协作立体视觉系统，利用两架无人机的宽基线空间配置实现长距离稠密建图。关键创新包括：(1) 双谱视觉惯性测距估计器，用于鲁棒基线估计；(2) 结合深度学习跨机匹配与光流内机跟踪的混合特征关联策略；(3) 从稀疏到稠密的深度恢复方案，通过指数拟合远距离三角化稀疏特征点，实现精确度量尺度建图。实验表明，Flying Co-Stereo 系统在70米范围内实现稠密3D建图，相对误差为2.3%-9.7%，深度范围比传统系统提升最高达350%，覆盖面积提升450%。
原文摘要 · Abstract (English)
Lightweight long-range mapping is critical for safe navigation of UAV swarms in large-scale unknown environments. Traditional stereo vision systems with fixed short baselines face limited perception ranges. To address this, we propose Flying Co-Stereo, a cross-agent collaborative stereo vision system that leverages the wide-baseline spatial configuration of two UAVs for long-range dense mapping. Key innovations include: (1) a dual-spectrum visual-inertial-ranging estimator for robust baseline estimation; (2) a hybrid feature association strategy combining deep learning-based cross-agent matching and optical-flow-based intra-agent tracking; (3) A sparse-to-dense depth recovery scheme,refining dense monocular depth predictions using exponential fitting of long-range triangulated sparse landmarks for precise metric-scale mapping. Experiments demonstrate the Flying Co-Stereo system achieves dense 3D mapping up to 70 meters with 2.3%-9.7% relative error, outperforming conventional systems by up to 350% in depth range and 450% in coverage area. The project webpage: https://xingxingzuo.github.io/flying_co_stereo
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