Abstract
Drone-based rapid and accurate environmental edge detection is highly advantageous for tasks such as disaster relief and autonomous navigation. Current methods, using radars or cameras, raise deployment costs and burden lightweight drones with high computational demands. In this paper, we propose AirTouch, a system that transforms the ground effect from a stability "foe" in traditional flight control views, into a "friend" for accurate and efficient edge detection. Our key insight is that analyzing drone basic attitude sensor readings and flight commands allows us to detect ground effect changes. Such changes typically indicate the drone flying over a boundary of two materials, making this information valuable for edge detection. We approach this insight through theoretical analysis, algorithm design, and implementation, fully leveraging the ground effect as a new sensing modality without compromising drone flight stability, thereby achieving accurate and efficient scene edge detection. We also compare this new sensing modality with vision-based methods to clarify its exclusive advantages in resource efficiency and detection capability. Extensive evaluations demonstrate that our system achieves a high detection accuracy with mean detection distance errors of 0.051m, outperforming the baseline method performance by 86%. With such detection performance, our system requires only 43 mW power consumption, contributing to this new sensing modality for low-cost and highly efficient edge detection.
Abstract (translated)
基于无人机的快速且准确的环境边缘检测对于诸如灾害救援和自主导航等任务非常有利。目前使用雷达或相机的方法会增加部署成本，并给轻型无人机带来高计算需求负担。在本文中，我们提出了AirTouch系统，该系统将地面效应从传统飞行控制视角中的稳定性“敌人”转变为精确高效边缘检测的“朋友”。我们的关键洞察是分析无人机基本姿态传感器读数和飞行指令可以让我们检测到地面效应的变化。这种变化通常表明无人机飞越了两种材料之间的边界，因此这些信息对于边缘检测非常有价值。我们通过理论分析、算法设计和实施来实现这一见解，并充分利用地面效应作为新的感测模式，同时不损害无人机的飞行稳定性，从而实现了精确高效的场景边缘检测。 此外，我们将这种方法与基于视觉的方法进行比较，以阐明其在资源效率和检测能力方面的独特优势。广泛的评估表明，我们的系统能够实现高精度的检测，平均检测距离误差仅为0.051米，优于基准方法86%。凭借这种检测性能，我们的系统仅需消耗43毫瓦功率，为低成本且高效的边缘检测提供了新的感测模式。
URL
https://arxiv.org/abs/2509.21085
