Skip to content
Open access

Improved 3D Gaussian splatting integrating VGGT and LiDAR: Application in visual relocalization for UAV inspection of large aircraft

Sep 2026 · AIP Advances · 0 citations · 30 references

Abstract

For high-precision unmanned aerial vehicle (UAV) visual relocalization in large-scale aircraft inspection, this paper proposes an improved 3DGS method integrating visual geometry grounded transformer (VGGT) with LiDAR and designs a coarse-to-fine two-stage image matching strategy to tackle the challenge. First, the low-rank adaptation technique is adopted to fine-tune the segment anything model (SAM3), and a dedicated dataset with refined aircraft structural features is constructed to achieve high-precision foreground segmentation of aircraft targets, which eliminates environmental interference for 3D mapping. Second, point clouds generated by VGGT are registered and fused with LiDAR point clouds, providing 3DGS with initialized data possessing real physical scales. Meanwhile, a smooth L1 depth loss is introduced to build a joint photometric–geometric optimization framework, so as to enhance the geometric consistency of the model. Finally, the pose estimation problem is converted into an image similarity matching problem. Coarse localization is realized through sparse sampling on multi-layer concentric hemispheres combined with dense matching via RoMa, while precise localization is completed by fusing feature distance, structural similarity index measure, and peak signal-to-noise ratio. Experimental results show that the improved SAM3 segmentation model achieves superior performance. The proposed improved 3DGS outperforms mainstream methods, including the original 3DGS, in rendering metrics and training efficiency. In addition, the presented pose estimation method achieves higher localization accuracy than HLoc, NeRF-Loc, and other comparative approaches in both indoor and outdoor scenarios. This method ensures high-precision and real-time mapping and localization, provides an effective scheme for aviation UAV intelligent inspection, and broadens the application of 3DGS in industrial automation.

Read PDF

Similar papers

2026

LDI-3DGS: Structurally Robust 3-D Gaussian Splatting Driven by UAV-Borne LiDAR Depth and Intensity Priors

3-D Gaussian splatting (3DGS) has demonstrated outstanding performance in novel view synthesis and 3-D scene reconstruction. While 3DGS can technically be optimized from random initialization, achieving high-quality and scale-accurate reconstruction in large-scale scenes still relies heavily on sparse structure-from-mo...

Tian-Jiao Wang, Qing-Zhou Mao, Zhi-Xin Duan et al. · 0 citations
Sep 2026

VDGS: Visibility-Driven Large-Scale 3D Gaussian Splatting for Aerial Scene Reconstruction

VDGS introduces visibility-driven statistics for scene anchors to quantify supervision strength and is leveraged for scene partitioning and for gradient compensation in under-optimized regions, thereby promoting balanced optimization across different regions.

Hao-Lin Yu, Jia-Dong Tang, Yi-Xian Wang et al. · 0 citations
Open access Sep 2026

PRI-Net: A Lightweight Multimodal Framework for 3D UAV Localization

PRI-Net is proposed, an efficient and lightweight multimodal fusion framework for UAV localization that integrates point cloud splatting, residual attention fusion, and an information bottleneck that achieves high localization accuracy with lightweight architectures, while reducing feature dimensionality and improving...

Zhi-Xuan Chen, Jia-Liang Lu, Zhong Ye et al. · 0 citations
Open access Sep 2026

Fine-Registration between Point Clouds and Aerial Images using Monocular Geometry

Accurate registration between aerial imagery and LiDAR point clouds is fundamental to building-level analysis and urban modeling. Although coarse alignment can be achieved through geo-referencing or sensor calibration, residual misalignment often remains and affects the reliable interpretation of roof structures. To ad...

Qi-Peng Mei, D. Bulatov, D. Iwaszczuk · 0 citations
Open access Aug 2026

Geo-Consistent Centralized Multi-UAV Gaussian SLAM for Incremental Orthophoto Generation

A centralized GNSS-assisted multi-UAV 3D Gaussian Splatting SLAM framework for online incremental orthophoto mapping that provides a favorable trade-off between geo-consistency, visual fidelity, and efficiency compared with existing methods is presented.

Xiao Zhang, Shuai-Xin Li, Hong-Bin Dong et al. · 0 citations
Open access Sep 2026

A Geometry-Constrained Framework for Automatic Geometric Positioning Accuracy Assessment of Large-Scale Satellite Imagery

A geometry-constrained framework that integrates Rational Polynomial Coefficient prior constraints, coarse-to-fine registration, adaptive match-density-based block selection, hierarchical geometric verification, and a geolocation residual confidence measure into a unified automatic quality inspection pipeline is propos...

Jia-Ming Cui, Wei-Bin Wang, Li-Ming Fan et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.