Abstract
Microscopic analysis of microparticles in situ in diverse water environments is necessary for monitoring water quality and localizing contamination sources. Conventional sensors such as optical microscopes and fluorometers often require complex sample preparation, are restricted to small sample volumes, and are unable to simultaneously capture all pertinent details of a sample such as particle size, shape, concentration, and three-dimensional motion. This paper proposes a novel and cost-effective robotic system for mobile microscopic analysis of particles in situ at various depths which are fully controlled by the robot system itself. A miniature underwater digital in-line holographic microscope (DIHM) performs high-resolution imaging of microparticles (e.g., algae cells, plastic debris, sediments) while movement allows measurement of particle distributions covering a large area of water.
Similar content being viewed by others
Code Availability
MATLAB implementation of the processing code is available at github.com/HongFFIL/rihvr-matlab.
References
Bochdansky, A.B., Jericho, M.H., Herndl, G.J.: Development and deployment of a point-source digital inline holographic microscope for the study of plankton and particles to a depth of 6000 m. Limnol. Oceanogr. Methods 11(JAN), 28–40 (2013)
Chengala, A.A., Hondzo, M., Troolin, D., Lefebvre, P.A.: Kinetic responses of Dunaliella in moving fluids. Biotechnol. Bioeng. 107(1), 65–75 (2010)
Cole, B.: Inquiry into amphibious screw traction. Proceedings of the Institution of Mechanical Engineers 175(1), 919–940 (1961)
Counihan, T.D., Bollens, S.M.: Early detection monitoring for larval dreissenid mussels: how much plankton sampling is enough? Environ. Monit. Assess. 189(3), 98 (2017)
Dhull, S., Canelon, D., Kottas, A., Dancs, J., Carlson, A., Papanikolopoulos, N.: Aquapod: A small amphibious robot with sampling capabilities. In: IEEE International Conference on Intelligent Robots and Systems, pp 100–105 (2012)
Dugoff, H., Robert Ehlich, I.: Model tests of bouyant screw rotor configurations. J. Terrramech. 4(3), 9–22 (1967)
El Mallahi, A., Minetti, C., Dubois, F.: Automated three-dimensional detection and classification of living organisms using digital holographic microscopy with partial spatial coherent source: application to the monitoring of drinking water resources. Appl. Opt. 52(1), A68–80 (2013)
Fales, W., Amick, D., Schreiner, B.: The riverine utility craft (ruc). J. Terrramech. 8(3), 23–38 (1972)
Gabor, D.: A new microscopic principle. Nature 161(4098), 777–778 (1948)
Gopalan, B., Malkiel, E., Katz, J.: Experimental investigation of turbulent diffusion of slightly buoyant droplets in locally isotropic turbulence car model. Phys. Fluids 20(9), 095102 (2008)
Göröc, Z., Tamamitsu, M., Bianco, V., Wolf, P., Roy, S., Shindo, K., Yanny, K., Wu, Y., Koydemir, H.C., Rivenson, Y., Ozcan, A.: A deep learning-enabled portable imaging flow cytometer for cost-effective, high-throughput, and label-free analysis of natural water samples. Light: Science & Applications 7(1), 66 (2018)
Graham, G., Nimmo-Smith, A.: The application of holography to the analysis of size and settling velocity of suspended cohesive sediments. Limnol. Oceanogr. Methods, 1–15 (2010)
Greenfield, D.I., Marin, R., Doucette, G.J., Mikulski, C., Jones, K., Jensen, S., Roman, B., Alvarado, N., Feldman, J., Scholin, C.: Field applications of the second-generation Environmental Sample Processor (ESP) for remote detection of harmful algae: 2006-2007. Limnol. Oceanogr. Methods 6(12), 667–679 (2008)
Hemes, B., Canelon, D., Dancs, J., Papanikolopoulos, N.: Robotic tumbling locomotion. IEEE Int. Conf. Robot. Autom., 5063–5069 (2011)
Howard, A., Sandler, M., Chu, G., Chen, L.c., Chen, B., Tan, M., Wang, W., Zhu, Y., Pang, R., Vasudevan, V., Le, Q.V., Adam, H.: Searching for MobileNetV3. International Conference on Computer Vision, 1314–1324 (2019)
Katz, J., Sheng, J.: Applications of holography in fluid mechanics and particle dynamics. Annu. Rev. Fluid Mech. 42(1), 531–555 (2010)
Kemppinen, O., Laning, J.C., Mersmann, R.D., Videen, G., Berg, M.J.: Imaging atmospheric aerosol particles from a UAV with digital holography. Sci. Rep. 10(1), 1–12 (2020)
Kinsey, J.C., Yoerger, D.R., Jakuba, M.V., Camilli, R., Fisher, C.R., German, C.R.: Assessing the deepwater horizon oil spill with the sentry autonomous underwater vehicle. IEEE International Conference on Intelligent Robots and Systems, 261–267 (2011)
Lindensmith, C.A., Rider, S., Bedrossian, M., Wallace, J.K., Serabyn, E., Showalter, G. M., Deming, J. W., Nadeau, J.L.: A submersible, off-axis holographic microscope for detection of microbial Motility and morphology in aqueous and icy environments. Plos One 11(1), e0147700 (2016)
Malek, M., Allano, D., Coëtmellec, S., Lebrun, D.: Digital in-line holography: influence of the shadow density on particle field extraction. Opt. Express 12(10), 2270–9 (2004)
Mallery, K., Hong, J.: Regularized inverse holographic volume reconstruction for 3D particle tracking. Opt. Express 27(13), 18069–18084 (2019)
Molaei, M., Barry, M., Stocker, R., Sheng, J.: Failed escape: Solid surfaces prevent tumbling of Escherichia coli. Phys. Rev. Lett. 113(6), 1–6 (2014)
Murphy, D. W., Li, C., D’Albignac, V., Morra, D., Katz, J.: Splash behaviour and oily marine aerosol production by raindrops impacting oil slicks. J. Fluid Mech. 780, 536–577 (2015)
Nagaoka, K., Kubota, T., Otsuki, M., Tanaka, S.: Development of lunar exploration rover using screw propulsion units -note on dynamic behavior and moving direction control. In: 19th Work. JAXA Astrodyn. Flight Mech., Kanagawa, Japan, pp 143–148 (2009)
Natagani, K., Kiribayashi, S., Okada, Y., Otake, K., Yoshida, K.: Emergency response to the nuclear accident at the Fukushima Daiichi nuclear power plants using mobile rescue robots. IFAC Proc. 7(PART 1), 81–86 (2007)
Neumann, P.P., Asadi, S., Lilienthal, A.J., Bartholmai, M., Schiller, J.H.: Autonomous gas-sensitive microdrone: Wind vector estimation and gas distribution mapping. IEEE Robot. Autom. Mag., 50–61 (2012)
Poon, T.C., Liu, J.P.: Introduction to modern digital holography with MATLAB. Cambridge University (2014)
Rowe, M.D., Anderson, E.J., Wynne, T.T., Stumpf, R.P., Fanslow, D.L., Kijanka, K., Vanderploeg, H.A., Strickler, J.R., Davis, T.W.: Vertical distribution of buoyant Microcystis blooms in a Lagrangian particle tracking model for short-term forecasts in Lake Erie. J. Geophys. Rese. Oceans, 1–19 (2016)
Sheng, J., Malkiel, E., Katz, J., Adolf, J., Belas, R., Place, A.R.: Digital holographic microscopy reveals prey-induced changes in swimming behavior of predatory dinoflagellates. Proc. Nat. Acad. Sci. U. S. A. 104(44), 17512–17517 (2007)
Sung, M., Yu, S.C.: Balloon AUV: seawater sampling AUV using active buoyancy control. AUV 2018 - 2018 IEEE/OES Autonomous Underwater Vehicle Workshop, Proceedings, pp. 19–23 (2018)
Talapatra, S., Hong, J., McFarland, M., Nayak, A., Zhang, C., Katz, J., Sullivan, J., Twardowski, M., Rines, J., Donaghay, P.: Characterization of biophysical interactions in the water column, using in situ digital holography. Mar. Ecol. Prog. Ser. 473, 29–51 (2012)
U.S. Environmental Protection Agency: A compilation of cost data associated with the impacts and control of nutrient pollution. Tech. Rep. May, U.S Environmental Protection Agency (2015)
Vincent, R.K., Qin, X., McKay, R.M.L., Miner, J., Czajkowski, K., Savino, J., Bridgeman, T.: Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie. Remote Sens. Environ. 89(3), 381–392 (2004)
Watson, J., Alexander, S., Craig, G., Hendry, D.C., Hobson, P.R., Lampitt, R.S., Marteau, J.M., Nareid, H., Player, M.A., Saw, K.: Simultaneous in-line and off-axis subsea holographic recording of plankton and other marine particles. Meas. Sci. Technol. 12, L9–L15 (2001)
Wilkinson, A.A., Hondzo, M., Guala, M.: Vertical heterogeneities of cyanobacteria and microcystin concentrations in lakes using a seasonal In situ monitoring station. Glob. Ecol. Conserv. 21, e00838 (2020)
Wynne, T.T., Stumpf, R.P., Tomlinson, M.C., Dyble, J.: Characterizing a cyanobacterial bloom in western Lake Erie using satellite imagery and meteorological data. Limnol. Oceanogr. 55(5), 2025–2036 (2010)
Acknowledgements
The authors would like to thank Jiaqi You, Anne Wilkinson, and Miki Hondzo for their knowledge of algae and assistance during deployments and David Brajkovic for work developing miniaturized holographic sensors. This work is supported by the National Science Foundation through grants #IIS-1427014, #CNS-1439728, #CNS-1531330, #CNS-1544887, and #CNS-1939033. USDA/NIFA has also supported this work through grant 2020-67021-30755.
Funding
This work is supported by the National Science Foundation through grants #IIS-1427014, #CNS-1439728, #CNS-1531330, #CNS-1544887, and #CNS-1939033. United States Department of Agriculture/ National Institute of Food and Agriculture has also supported this work through grant 2020-67021-30755.
Author information
Authors and Affiliations
Contributions
All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Kevin Mallery, and Dario Canelon. The first draft of the manuscript was written by Kevin Mallery and Dario Canelon and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of Interests
The authors declare that they have no conflict of interest.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mallery, K., Canelon, D., Hong, J. et al. Design and Experiments with a Robot-Driven Underwater Holographic Microscope for Low-Cost In Situ Particle Measurements. J Intell Robot Syst 102, 32 (2021). https://doi.org/10.1007/s10846-021-01404-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10846-021-01404-3