Predicting Digging Success for Unmanned Aircraft System Sensor Emplacement

Conference paper
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 11)


We have developed an autonomous, digging, Unmanned Aircraft System (UAS) for sensor emplacement. A key challenge is quickly determining whether or not a particular digging activity will lead to successful emplacement, thereby allowing the system to potentially try another location. We have designed a first-of-its-kind decision-making algorithm using a Markov Decision Process to autonomously monitor the activity of a digging UAS activity to quickly decide if success is likely. Further, we demonstrate through many experimental trials that our method outperforms other decision-making methods with an overall success rate of 82.5%.


Sensor emplacement UAS Field robotics Markov Decision Process 



Thanks to Dr. Sebastian Elbaum, Dr. Brittany Duncan, Andrew Rasmussen, Ajay Shankur, Jacob Hogberg, and Aaron Clare and the staff at Horning State Farm for their assistance.

Supplementary material

Supplementary material 1 (mp4 18304 KB)


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Computer Science and Engineering DepartmentUniversity of NebraskaLincolnUSA
  2. 2.Mechanical Engineering DepartmentUniversity of NebraskaLincolnUSA

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