Unmanned Aerial Vehicle-Based Wireless Charging of Sensor Networks

  • Carrick DetweilerEmail author
  • Michael Eiskamp
  • Brent Griffin
  • Jennifer Johnson
  • Jinfu Leng
  • Andrew Mittleider
  • Elizabeth Basha


Sensor networks deployed in remote and hard to access locations often require regular maintenance to replace or charge batteries as solar panels are sometimes impractical. In this chapter, we develop an Unmanned Aerial Vehicle (UAV) that can fly to remote locations to charge sensors using magnetic resonant wireless power transfer. We discuss the challenges of using UAVs to charge sensors wirelessly. We then present the design of a lightweight system that can be carried by a UAV as well as design a localization sensor and algorithm to allow the UAV to precisely align itself with the receiver by sensing the induced field. We also develop a number of algorithms to address the question of which sensors should be charged given a network of sensors. Finally, we experimentally verify algorithms that leverage the sensor network’s ability to adapt internal communication and energy consumption patterns to optimize UAV-based wireless charging.


Sensor Network Sensor Node Wireless Sensor Network Optical Flow Unmanned Aerial Vehicle 
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.



This work was partially supported by NSF 1217400, NSF 1217428, and USDA-NIFA 2013-67021-20947.


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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Carrick Detweiler
    • 1
    Email author
  • Michael Eiskamp
    • 2
  • Brent Griffin
    • 3
  • Jennifer Johnson
    • 2
  • Jinfu Leng
    • 1
  • Andrew Mittleider
    • 1
  • Elizabeth Basha
    • 2
  1. 1.Nebraska Intelligent MoBile Unmanned Systems (NIMBUS) Lab, Department of Computer Science and EngineeringUniversity of Nebraska-LincolnLincolnUSA
  2. 2.Department of Electrical and Computer EngineeringUniversity of the PacificStocktonUSA
  3. 3.Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborUSA

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