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Behavior-Tree-Based Person Search for Symbiotic Autonomous Mobile Robot Tasks

Marvin Stuede*, Timo Lerche, Martin Alexander Petersen, Svenja Spindeldreier

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Abstract

We consider the problem of people search by a mobile social robot in case of a situation that cannot be solved by the robot alone. Examples are physically opening a closed door or operating an elevator. Based on the Behavior Tree framework, we create a modular and easily extendable action sequence with the goal of finding a person to assist the robot. By decomposing the Behavior Tree as a Discrete Time Markov Chain, we obtain an estimate of the probability and rate of success of the options for action, especially where the robot should wait or search for people.In a real-world experiment, the presented method is compared with other common approaches in a total of 588 test runs over the course of one week, starting at two different locations in a university building. We show our method to be superior to other approaches in terms of success rate and duration until a finding person and returning to the start location.
Original languageEnglish
Title of host publicationProceedings of the 2021 IEEE International Conference on Robotics and Automation (ICRA)
PublisherIEEE
Pages2414-2420
Number of pages7
ISBN (Electronic)978-1-7281-9077-8
ISBN (Print)978-1-7281-9078-5
DOIs
Publication statusPublished - 16 Mar 2021
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an International Convention and Exhibition Center, Xi'an, China
Duration: 30 May 20215 Jun 2021

Publication series

NameProceedings. Robotics and automation
PublisherIEEE
ISSN (Print)1050-4729
ISSN (Electronic)2577-087X

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Abbreviated titleICRA 2021
Country/TerritoryChina
CityXi'an
Period30 May 20215 Jun 2021

Keywords

  • cs.RO

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

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