Sensing Water Properties at Precise Depths from the Air

  • John-Paul OreEmail author
  • Carrick Detweiler
Conference paper
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 5)


Water properties critical to our understanding and managing of freshwater systems change rapidly with depth. This work presents an Unmanned Aerial Vehicle (UAV) based method of keeping a passive, cable-suspended sensor payload at a precise depth, with \(95\%\) of submerged sensor readings within \(\pm 8.4\,\text {cm}\) of the target depth, helping dramatically increase the spatiotemporal resolution of water science datasets. We use a submerged depth altimeter attached at the terminus of a \(3.5\,\text {m}\) semi-rigid cable as the sole input to a depth controller actuated by the UAV’s motors. First, we simulate the system and common environmental disturbances of wind, water, and GPS drift and then use parameters discovered during simulation to guide implementation. In field experiments, we compare the depth precision of our new method to previous methods that used the UAV’s altitude as a proxy for submerged sensor depth, specifically: (1) only using the UAV’s air-pressure altimeter; and (2) fusing UAV-mounted ultrasonic sensors with the air-pressure altimeter. Our new method reduces the standard deviation of depth readings by \(75\%\) in winds up to \(8\,\text {m/s}\). We show the step response of the depth-altimeter method when transitioning between target depths and show that it meets the precision requirements. Finally, we explore a longer, \(8.0\,\text {m}\) cable and show that our depth-altimeter method still outperforms previous methods and allows scientists to increase the spatiotemporal resolution of water property datasets.


Water Properties Unmanned Aerial Vehicles (UAV) Sensor Payload Target Depth Depth Readings 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Thanks to Dr. Sebastian Elbaum and Dr. Justin Bradley for insightful discussions. Becca Horzewski helped design and build the underwater sensor. For help with field experiments we thank Ajay Shankar, Ashraful Islam, Adam Plowcha, Chandima Fernando, and Nishant Sharma. This work partially supported by NSF NRI-1638099, USDA-NIFA 2013-67021-20947 and USDA-NIFA 2017-67021-25924.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Computer Science and EngineeringUniversity of Nebraska-LincolnLincolnUSA

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