水下
机器人
仿生学
计算机科学
流量(数学)
唤醒
振荡(细胞信号)
工作(物理)
声学
度量(数据仓库)
对象(语法)
流量传感器
仿生材料
信息流
适应(眼睛)
人工智能
机器人学
控制工程
海洋工程
计算机视觉
作者
Myungsun Park,A. Chen,Jacobo Cervera-Torralba,Michael T. Tolley,Geno Pawlak
出处
期刊:Science Advances
[American Association for the Advancement of Science]
日期:2026-06-03
卷期号:12 (23): eaed2847-eaed2847
标识
DOI:10.1126/sciadv.aed2847
摘要
We address the challenge of sensing self-motion and environmental information by autonomous underwater vehicles. To overcome the limitations of conventional sensing methods in terms of size, cost, and environmental restrictions, previous work has investigated biomimetic flow sensors. Challenges in application of those biomimetic sensors include measuring complex locomotion of the vehicles and detecting external flow structure during the motion, all within a compact form suitable for a small vehicle. To address the challenges, we present a small and lightweight soft magnetic hair flow sensor that can measure the speed, direction, and oscillation of flow based on its mechanical deflection. We tested the ability of these sensors on underwater robots to estimate their forward, lateral (angular) speeds and orientations. While the robots were swimming, the sensors could also detect the wake behind an upstream object by identifying its characteristic frequency. The bioinspired hydrodynamic sensing, as demonstrated with the proposed sensors in this article, could allow adaptive and efficient underwater exploration.
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