Predicting Digging Success for Unmanned Aircraft System Sensor Emplacement

Adam Plowcha, Yue Sun, Carrick Detweiler, Justin Bradley

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

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%.

Original languageEnglish (US)
Title of host publicationSpringer Proceedings in Advanced Robotics
PublisherSpringer Science and Business Media B.V.
Pages153-164
Number of pages12
DOIs
StatePublished - 2020

Publication series

NameSpringer Proceedings in Advanced Robotics
Volume11
ISSN (Print)2511-1256
ISSN (Electronic)2511-1264

Keywords

  • Field robotics
  • Markov Decision Process
  • Sensor emplacement
  • UAS

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Engineering (miscellaneous)
  • Artificial Intelligence
  • Computer Science Applications
  • Applied Mathematics

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