SpatialFly: Implicit 3D Prior-Guided Visual Reparameterization for Continuous UAV Vision-and-Language Navigation

2026-03-22 · Source: cs.CV updates on arXiv.org · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Robotics & Autonomous Systems · Depth: Expert, quick

Summary

SpatialFly is a novel geometry-guided spatial representation framework designed to enhance Unmanned Aerial Vehicle (UAV) Vision-and-Language Navigation (VLN) in complex 3D environments. Addressing the mismatch between 2D visual perception and 3D trajectory decision space, SpatialFly operates directly on RGB observations without requiring explicit 3D reconstruction. It employs a geometry-guided 2D adaptive representation mechanism, featuring a geometric prior injection module that integrates global structural cues into 2D semantic tokens for scene-level guidance. A subsequent geometry-aware reparameterization module then adaptively reparameterizes visual tokens using geometry-conditioned cross-modal attention and gated residual fusion. Experimental results demonstrate SpatialFly's superior performance, reducing Navigation Error (NE) by 4.03m and improving Success Rate (SR) by 1.27% over the strongest baseline on the unseen Full split, while also yielding smoother, more stable trajectories.

Key takeaway

For robotics engineers developing UAV navigation systems, particularly in complex 3D environments, SpatialFly offers a significant advancement. If you are struggling with the structural mismatch between 2D visual perception and 3D trajectory decisions, you should consider implementing geometry-guided visual reparameterization. This approach improves navigation accuracy, reducing errors by 4.03m and increasing success rates by 1.27% without requiring explicit 3D reconstruction, leading to more stable and aligned UAV trajectories.

Key insights

SpatialFly enhances UAV Vision-and-Language Navigation by integrating implicit 3D geometric priors into 2D visual representations, avoiding explicit 3D reconstruction.

Principles

• Bridge 2D perception and 3D decision space.
• Inject global structural cues into 2D tokens.
• Adaptive reparameterization improves visual tokens.

Method

SpatialFly employs a geometry-guided 2D adaptive representation. It injects global structural cues into 2D semantic tokens and adaptively reparameterizes visual tokens using geometry-conditioned cross-modal attention and gated residual fusion.

In practice

• Enhance UAV autonomous exploration.
• Improve disaster response navigation.
• Enable smoother infrastructure inspection.

Topics

• UAV Navigation
• Vision-and-Language Navigation
• 3D Geometric Priors
• Visual Reparameterization
• Autonomous Robotics
• Computer Vision

Best for: Research Scientist, AI Scientist, Machine Learning Engineer, Computer Vision Engineer

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Editorial summary, takeaway, and curation by AIssential. Original article published by cs.CV updates on arXiv.org.