Terrain-Aware Adaptation for Two-Dimensional UAV Path Planners

TL;DR

This paper introduces a modular terrain-aware extension to 2D UAV path planners, improving 3D reconstruction quality by adjusting altitude and camera orientation, demonstrated through simulations and real-world tests.

Contribution

It extends existing 2D path planning algorithms to incorporate terrain awareness, enhancing 3D reconstruction around vertical and occluded surfaces.

Findings

Improved 3D reconstructions in vertical and occluded areas.

Consistent performance gains demonstrated in simulations and real-world tests.

Open-source implementation available for further research.

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 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