Battery-constrained coverage

Saurabh Mishra, Samuel Rodriguez, Marco Morales, Nancy M. Amato

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this work, we present a behavioral modeling framework and coverage behavior that accounts for a battery constraint. This framework allows a user to model robot teams performing common robotic tasks such as exploration. It uses roadmap-based methods that identify the available paths in potentially complex environments. We present a coverage strategy that accounts for the available battery. It allows the agent to calculate a path through an environment that maximizes coverage and allows the agent to get back to a charging location. This eliminates the need to decide when to return to a charging location based on a threshold, as related methods do. It considers the actual path length as opposed to Euclidean distance which is generally used for estimating the energy spent in traversing a path. Different path scoring functions are used to score the path generated.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
PublisherIEEE Computer Society
Pages695-700
Number of pages6
ISBN (Electronic)9781509024094
DOIs
StatePublished - Nov 14 2016
Externally publishedYes
Event2016 IEEE International Conference on Automation Science and Engineering, CASE 2016 - Fort Worth, United States
Duration: Aug 21 2016Aug 24 2016

Publication series

NameIEEE International Conference on Automation Science and Engineering
Volume2016-November
ISSN (Print)2161-8070
ISSN (Electronic)2161-8089

Conference

Conference2016 IEEE International Conference on Automation Science and Engineering, CASE 2016
Country/TerritoryUnited States
CityFort Worth
Period8/21/168/24/16

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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