Home /Research /Terrain-Aware Adaptation for Two-Dimensional UAV Path Planners
SWARM

Terrain-Aware Adaptation for Two-Dimensional UAV Path Planners

Kostas Karakontis, Thanos Petsanis, Athanasios Ch. Kapoutsis, Pavlos Ch. Kapoutsis, Elias B. Kosmatopoulos

Year
2025
Citations
1

Abstract

Multi-UAV Coverage Path Planning (mCPP) algorithms in popular commercial software typically treat a Region of Interest (RoI) only as a 2D plane, ignoring important 3D structure characteristics. This leads to incomplete 3D reconstructions, 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

Keywords

TerrainAdaptation (eye)Computer sciencePath (computing)Motion planningReal-time computingHuman–computer interactionSimulationArtificial intelligenceRobot

Related papers

Browse all SWARM papers