Integration, Calibration, and Experimental Verification of a Speed Sensor for Swimming Animals

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  • Joaquin Gabaldon, University of Michigan, Ann Arbor, Michigan.
  • ,
  • Ellen L. Turner, The Pennsylvania State University, Grove City College
  • ,
  • Matthew Johnson-Roberson, University of Michigan, Ann Arbor, Michigan.
  • ,
  • Kira Barton, University of Michigan, Ann Arbor, Michigan.
  • ,
  • Mark Johnson
  • Erik J. Anderson, Grove City College, Woods Hole Oceanographic Institution
  • ,
  • K. Alex Shorter, University of Michigan, Ann Arbor, Michigan.

Animal-attached GPS loggers are used to monitor the movement of land animals, but obtaining the measurements of aquatic animals remains challenging. Current animal-attached speed sensors are placed close to the body and measure the speed of the disturbed fluid near the skin interface, potentially affecting the accuracy of the measurement. Furthermore, the absolute speed estimates derived from the sensor data are affected by the location on the animal, orientation with respect to flow, and device shape. Here, we evaluate the performance of a micro-turbine in both the steady and variable flows using particle image velocimetry to visualize and measure the flow field around the tag and sensor. A closed recirculating flume was used to generate a range of both steady and oscillating flows at the sensor. During steady flow, turbine rotation rate was linearly correlated with both the free stream and near-sensor flow speeds. Following the controlled measurements of fluid speed in the flume, a tag with the speed sensor was used to measure both the speed and the total distance traveled by the dolphins in a managed environment. The results compared well with the speed and distance made from the analysis of video collected by an overhead camera system. Finally, the measurement variability of four specially designed tags with speed sensors was tested in the towing tank in the Marine Hydrodynamics Laboratory at the University of Michigan. These results provide a foundation for interpreting in-situ speed measurements from swimming animals, and potentially autonomous underwater vehicles, and will guide the development of the improved algorithms for the localization and energetics estimation.

Original languageEnglish
Article number8629066
JournalIEEE Sensors Journal
Volume19
Issue10
Pages (from-to)3616-3625
Number of pages10
ISSN1530-437X
DOIs
Publication statusPublished - 2019

    Research areas

  • dead reckoning, localization, Odometry, persistent monitoring

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