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arXiv · 2505.07141

Terrain-aware Low Altitude Path Planning

Yixuan Jia·Andrea Tagliabue·Annika Thomas·Navid Dadkhah Tehrani·Jonathan P. How
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Abstract

In this paper, we study the problem of generating low-altitude path plans for nap-of-the-earth (NOE) flight in real time with only RGB images from onboard cameras and the vehicle pose. We propose a novel training method that combines behavior cloning and self-supervised learning, where the self-supervision component allows the learned policy to refine the paths generated by the expert planner. Simulation studies show 24.7% reduction in average path elevation compared to the standard behavior cloning approach.

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Yixuan Jia, Andrea Tagliabue, Annika Thomas, Navid Dadkhah Tehrani, Jonathan P. How. 2025-05-11. Terrain-aware Low Altitude Path Planning. https://arxiv.org/abs/2505.07141

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