High-resolution outdoor videography of insects using Fast Lock-On tracking
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.
Authors
- Victor V. Titov (ORCID: https://orcid.org/0000-0002-3000-8471)
- Michael J. M. Harrap (ORCID: https://orcid.org/0000-0003-0515-2348)
- Andrew Straw (ORCID: https://orcid.org/0000-0001-8381-0858)
- T. Thang Vo‐Doan (ORCID: https://orcid.org/0000-0002-5065-5887)
- Stephan Lochner (ORCID: https://orcid.org/0009-0001-9429-688X)
Institutions
- University of Freiburg (DE)
- Bernstein Center for Computational Neuroscience Freiburg (DE)
Publication Details
- Journal
- Science Robotics
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1126/scirobotics.adm7689
- Citations
- 16
- Primary Topic
- Plant and animal studies
- Type
- article
- Field-Weighted Citation Impact
- 16.47