表征野生动物对仿生与传统水下航行器的响应
Characterizing Wildlife Response to Biomimetic and Conventional Underwater Vehicles
- University of Colorado at Boulder（科罗拉多大学博尔德分校）
- Case Western Reserve University（凯斯西储大学）
- Woods Hole Oceanographic Institution（伍兹霍尔海洋研究所）
- Massachusetts Institute of Technology（麻省理工学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究首次比较鱼类对传统与仿生AUV及潜水员的干扰响应，发现仿生AUV略优，提供首个量化仿生机器人生态影响的数据集与基准。
AI中文摘要：
自主水下航行器（AUV）是可扩展收集自然海洋生态数据的一种有前景的潜水员替代方案。然而，这些机器人可能会干扰当地动物群，并与其他监测技术相比引起剧烈的行为差异，从而降低其作为科学工具的价值。一个前景广阔的方向是制造更具仿生性的AUV，希望采用非捕食性动物的形态和行为可以减少不良响应。我们提出了首个比较鱼类对传统螺旋桨驱动AUV、海龟启发式鳍驱动AUV和潜水员干扰响应的数据集。实验在加勒比珊瑚礁的生物多样性热点区域进行，使用计算机视觉分析场景图像，以定位和研究鱼类行为变化。两种AUV均引起鱼类行为的可测量变化。尽管在多重比较校正后，机器人之间的差异不再显著，但点估计总体上偏向仿生AUV，这促使开展更大规模的研究以解决中等效应，并进一步优化设计以减少干扰。我们还观察到潜水员横断面期间的响应大于AUV横断面期间，尽管这一探索性比较基于样本量较小且存在多个混杂因素的潜水员数据。由于操作和实验限制，结论必须视为初步结果，但本研究为社区提供了首个已知数据集和基准，用于量化仿生机器人在野外生态监测中的行为影响。
英文摘要：
Autonomous underwater vehicles (AUVs) are a promising alternative to divers for scalable collection of natural ocean ecology data. However, these robots may disturb local fauna and cause drastic behavioral differences compared to other monitoring techniques, decreasing their value as scientific tools. A promising prospect is to make AUVs that are more biomimetic, with the hope that taking on the form and behavior of a non-predatory animal may reduce adverse responses. We present the first dataset comparing fish disturbance in response to a conventional thruster-driven AUV, a sea turtle inspired flipper-driven AUV, and a diver. Experiments were conducted at a biodiversity hotspot in a Caribbean reef, and images of the scene were analyzed using computer vision to localize and study fish behavior change. Both AUVs cause measurable changes in fish behavior. Although no between-robot differences remain significant after correction for multiple comparisons, point estimates generally favor the biomimetic AUV, motivating larger studies capable of resolving modest effects and further design changes to optimize for disturbance. We also observe larger responses during diver transects than during AUV transects, although this exploratory comparison is based on a small diver sample with several confounds. While conclusions must be taken as preliminary due to operational and experimental limitations, this study provides the community with a first known dataset and benchmarks to quantify the behavioral impacts of biomimetic robots for ecological monitoring in the wild.
