The bioinspiration lab develops instruments and techniques to explore mysteries of the deep sea for bioinspired design. With a focus on imaging, our technologies reveal novel views of marine organisms not otherwise possible, which we use to study the amazing adaptations animals have developed for life in a deep, cold, and dark environment.

We bring the laboratory into the ocean by developing minimally invasive techniques to understand physical-biological interaction using fine-scale measurements of organismal behavior in their natural environment. This instrumentation includes DeepPIV, a laser-based 2D imaging system that can be used to look through transparent tissues, and EyeRIS, a plenoptic camera system capable of imaging particle fields and tissue surface movement in 3D. In addition to these systems developed for deployment up to 4000 meter deep using remotely operated vehicles, we’re developing similar instrumentation for autonomous underwater vehicles to increase the spatial and temporal scale of our observations. Furthering the usefulness of these integrations, we’ve worked on enabling and integrating machine learning approaches to processing visual data through projects such as FathomNet and ML-tracking.

We also bring the ocean into the laboratory by using both novel and commonly used diagnostic engineering techniques to study biological and physical processes in more detail in a controlled environment, including shore-based and shipboard labs. This includes setups that use lasers or other advanced light sources to study morphology, locomotion, and fluid interactions in detail using highspeed cameras.

The lessons we learn during in-situ and laboratory studies can be used to improve ocean technology that advances exploration and discovery of our vastly underexplored ocean.

To bring the laboratory into the ocean, we develop less-invasive techniques to understand biological-physical interactions by furthering fine-scale measurements of organismal behavior and their physical and chemical environments. 

  • DeepPIV is an instrument that allows for high temporal and spatial resolution measurements of fluid motion that serves as a proxy for energetics, forces generated, transport, and performance (with Alana Sherman and Bruce Robison, MBARI). Deep particle Image Velocimetry (DeepPIV) has been used in novel ways to reconstruct 3D gelatinous structures using structured light.

  • Additional instrumentation developments in the short- and long-term involve coupling behavioral and environmental sensors (e.g., accelerometers, magnetometers, temperature, depth, salinity, light, dissolved oxygen) on minimally invasive platforms [ITAG: tagging package, collaboration with Aran Mooney (Woods Hole Oceanographic Institution) and Alex Shorter (University of Michigan), funded by The National Science Foundation Instrument Development for Biological Research program NSF-IDBR]

  • Mesobot: stereo tracking underwater vehicle, collaboration with Dana Yoerger (Woods Hole Oceanographic Institution) and Steve Rock (Stanford University), funded by The National Science Institute Ocean Technology and Interdisciplinary Coordination Program NSF-OTIC to allow for quantification of organismal behaviors (e.g., swimming, feeding, reproduction) in response to the environment (e.g., thermoclines, oxygen minimum zones) to understand when organismal behaviors are selected in specific environmental conditions, and to predict organismal response to a changing ocean.

To bring the ocean into the laboratory, we employ both cutting edge and commonly used diagnostic techniques in engineering to study biological and physical processes in more detail. We collect organisms using SCUBA and ROVs and transport them into the laboratory to further investigate features that cannot be adequately understood using in situ methods. This is an active area of research with collaborative efforts on understanding

  • Giant larvacean ecology (with Bruce Robison, MBARI),

  • Tomopterid fluid interactions to enable agile swimming and maneuvering (with Karen Osborn, Smithsonian),

  • Mechanisms behind swimming by prayiid siphonophores (with Jack Costello and Sean Colin), arguably the largest organisms on our planet, and

  • Fluid interactions with benthic filter feeders (with James Barry, MBARI).

In addition, using small-scale robotics, rapid prototyping, and advanced, optically clear and soft materials, we can design and build mechanical mimics to investigate how marine systems function in detail, and evaluate optimization and performance. Not only do these mechanical mimics contribute to the understanding of systems being studied, they will also streamline the technological pipeline to apply these lessons learned more rapidly to underwater technology.

Team

Publications

Katija, Kakani, E. Orenstein, B. Schlining, L. Lundsten, K. Barnard, G. Sainz, O. Boulais, M. Cromwell, E. Butler, B. Woodward, and K.L.C. Bell. 2022. FathomNet: A global image database for enabling artificial intelligence in the ocean. Scientific Reports, 12(15914): 114. https://doi.org/10.1038/s41598-022-19939-2

Masmitja, I., M. Martin, K. Katija, S. Gomariz, and J. Navarro. 2022. A reinforcement learning path planning approach for range-only underwater target localization with autonomous vehicles. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), Mexico City, Mexico, August 2022, 675–682. IEEE. https://doi.org/10.1109/CASE49997.2022.9926499

Cones, S.F., D. Zhang, K.A. Shorter, K. Katija, D.A. Mann, F.H. Jensen, J. Fontes, P. Afonso, and T.A. Mooney. 2022. Swimming behaviors during diel vertical migration in veined squid Loligo forbesii. Marine Ecology Progress Series, 691: 83–96. https://doi.org/10.3354/meps14056

Katija, K., E. Orenstein, B. Schlining, L. Lundsten, K. Barnard, G. Sainz, O. Boulais, B. Woodward, and K.C. Bell. 2021. FathomNet: A global underwater image training set for enabling artificial intelligence in the ocean. arXiv: 2109.14646. https://doi.org/10.48550/arXiv.2109.14646

Daniels, J., N. Aoki, J. Havassy, K. Katija, and K.J. Osborn. 2021. Metachronal swimming with flexible legs: A kinematics analysis of the midwater Polychaete Tomopteris. Integrative and Comparative Biology, 61: 1658–1673. https://doi.org/10.1093/icb/icab059

Technologies