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Terrain-Aware Adaptation for Two-Dimensional UAV Path Planners

Published: July 23, 2025 | arXiv ID: 2507.17519v2

By: Kostas Karakontis , Thanos Petsanis , Athanasios Ch. Kapoutsis and more

Potential Business Impact:

Drones map buildings better by flying smarter.

Business Areas:
Drone Management Hardware, Software

Multi-UAV Coverage Path Planning (mCPP) algorithms in popular commercial software typically treat a Region of Interest (RoI) only as a 2D plane, ignoring important3D structure characteristics. This leads to incomplete 3Dreconstructions, especially around occluded or vertical surfaces. In this paper, we propose a modular algorithm that can extend commercial two-dimensional path planners to facilitate terrain-aware planning by adjusting altitude and camera orientations. To demonstrate it, we extend the well-known DARP (Divide Areas for Optimal Multi-Robot Coverage Path Planning) algorithm and produce DARP-3D. We present simulation results in multiple 3D environments and a real-world flight test using DJI hardware. Compared to baseline, our approach consistently captures improved 3D reconstructions, particularly in areas with significant vertical features. An open-source implementation of the algorithm is available here:https://github.com/konskara/TerraPlan

Country of Origin
🇬🇷 Greece

Repos / Data Links

Page Count
6 pages

Category
Computer Science:
Robotics