Persistent ocean monitoring with underwater gliders: Adapting sampling resolution

  • Authors:
  • Ryan N. Smith;Mac Schwager;Stephen L. Smith;Burton H. Jones;Daniela Rus;Gaurav S. Sukhatme

  • Affiliations:
  • School of Engineering Systems, Queensland University of Technology, Brisbane, Queensland 4000, Australia;GRASP Lab, University of Pennsylvania, Philadelphia, Pennsylvania 19104;Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada;usCLab—The Burt Jones Group, University of Southern California, Los Angeles, California 90089;Distributed Robotics Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139;Robotic Embedded Systems Laboratory, University of Southern California, Los Angeles, California 90089

  • Venue:
  • Journal of Field Robotics
  • Year:
  • 2011

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Abstract

Ocean processes are dynamic and complex and occur on multiple spatial and temporal scales. To obtain a synoptic view of such processes, ocean scientists collect data over long time periods. Historically, measurements were continually provided by fixed sensors, e.g., moorings, or gathered from ships. Recently, an increase in the utilization of autonomous underwater vehicles has enabled a more dynamic data acquisition approach. However, we still do not utilize the full capabilities of these vehicles. Here we present algorithms that produce persistent monitoring missions for underwater vehicles by balancing path following accuracy and sampling resolution for a given region of interest, which addresses a pressing need among ocean scientists to efficiently and effectively collect high-value data. More specifically, this paper proposes a path planning algorithm and a speed control algorithm for underwater gliders, which together give informative trajectories for the glider to persistently monitor a patch of ocean. We optimize a cost function that blends two competing factors: maximize the information value along the path while minimizing deviation from the planned path due to ocean currents. Speed is controlled along the planned path by adjusting the pitch angle of the underwater glider, so that higher resolution samples are collected in areas of higher information value. The resulting paths are closed circuits that can be repeatedly traversed to collect long-term ocean data in dynamic environments. The algorithms were tested during sea trials on an underwater glider operating off the coast of southern California, as well as in Monterey Bay, California. The experimental results show improvements in both data resolution and path reliability compared to previously executed sampling paths used in the respective regions. © 2011 Wiley Periodicals, Inc. © 2011 Wiley Periodicals, Inc.