录像
无人机
四轴飞行器
计算机视觉
计算机科学
人工智能
多光谱图像
跟踪(教育)
实时计算
昆虫飞行
跟踪系统
弹道
遥感
生物
卡尔曼滤波器
地理
工程类
物理
航空航天工程
业务
天文
广告
遗传学
教育学
心理学
空气动力学
作者
T. Thang Vo‐Doan,Victor V. Titov,Michael J. M. Harrap,Stephan Lochner,Andrew Straw
出处
期刊:Science robotics
[American Association for the Advancement of Science]
日期:2024-10-16
卷期号:9 (95): eadm7689-eadm7689
被引量:13
标识
DOI:10.1126/scirobotics.adm7689
摘要
Insects have important roles globally in ecology, economy, and health, yet our understanding of their behavior remains limited. Bees, for example, use vision and a tiny brain to find flowers and return home, but understanding how they perform these impressive tasks has been hampered by limitations in recording technology. Here, we present Fast Lock-On (FLO) tracking. This method moves an image sensor to remain focused on a retroreflective marker affixed to an insect. Using paraxial infrared illumination, simple image processing can localize the sensor location of the insect in a few milliseconds. When coupled with a feedback system to steer a high-magnification optical system to remain focused on the insect, a high–spatiotemporal resolution trajectory can be gathered over a large region. As the basis for several robotic systems, we show that FLO is a versatile idea that can be used in combination with other components. We demonstrate that the optical path can be split and used for recording high-speed video. Furthermore, by flying an FLO system on a quadcopter drone, we track a flying honey bee and anticipate tracking insects in the wild over kilometer scales. Such systems have the capability to provide higher-resolution information about insects behaving in natural environments and as such will be helpful in revealing the biomechanical and neuroethological mechanisms used by insects in natural settings.
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