Iterative Hybrid Discrete-Continuous Viewpoint Planning for UAV Photogrammetry

2026-08-06

AI Summary

This work addresses the limitations of conventional UAV flight paths in complex geometric environments, which often result in inaccurate and incomplete 3D reconstructions. To overcome this, the authors propose an iterative hybrid discrete-continuous viewpoint planning method that leverages a proxy reconstruction model to guide viewpoint generation toward weakly observed regions while incorporating a redundancy elimination mechanism. A heuristic scoring function is introduced, integrating frontality, imaging distance, disparity, and multi-view observation count to evaluate candidate viewpoints. The global viewpoint set is further refined through visibility, overlap ratio, and graph connectivity constraints, with viewpoint layout optimized via a clustered CMA-ES algorithm. Evaluated on three synthetic scenes, the proposed approach significantly outperforms existing methods, achieving concurrent improvements in both reconstruction accuracy and completeness.

Abstract

Unmanned aerial vehicle (UAV) photogrammetry requires camera networks that provide sufficient surface coverage, image overlap, parallax, and resolution, yet conventional flight patterns are often poorly adapted to scene geometry resulting in local reconstruction errors. This paper proposes an iterative hybrid discrete-continuous viewpoint planning method for targeted UAV photogrammetry from a proxy reconstruction. The method scores sampled surface points using photogrammetric heuristics based on frontality, imaging distance, parallax, and multi-view observation count, while also evaluating the full viewpoint set in terms of visibility, pairwise overlap, and graph connectivity. Candidate viewpoints are generated around weakly observed regions, refined using clustered Covariance matrix adaptation evolution strategy (CMA-ES) optimisation, and removed when redundant. The final flight path combines close-range detail viewpoints with wider model-coverage viewpoints, balancing local reconstruction quality with global image-network robustness. Evaluation on three synthetic scenes shows that the proposed method improves both reconstruction accuracy and completeness compared with prior UAV path-planning methods.

Problem

• UAV photogrammetry
• viewpoint planning
• reconstruction errors
• scene geometry
• image overlap

Innovation

• viewpoint planning
• UAV photogrammetry
• CMA-ES optimization
• hybrid discrete-continuous
• reconstruction quality