Fleet size of multi-robot systems for exploration of structured environments

Flavio Cabrera-Mora, Jizhong Xiao

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

1 Scopus citations

Abstract

The fleet size of a multi-robot system is an important parameter to be considered for real robotics applications since it will determine the cost and the time of execution of any given task. Unfortunately, it is a topic that has received little attention in the robotics literature. The study of the fleet size will allow for the design and implementation of more effective techniques and coordination methods for multi-robot systems. In this paper we study the effects of the fleet size on the time of exploration of a structured environment. We present an analysis that allows us to specify the maximum fleet size that provides the maximum reduction on the exploration time when the structured environment is modeled as a tree. The analysis is applied to the Multi-Robot Depth First Search (MR-DFS) algorithm that allows for maximum parallelism when an exploration process starts from a single point. The analysis provides an expression for the average time of exploration of a tree and for the maximum number of robots that produces a significant reduction on the exploration time.

Original languageEnglish (US)
Title of host publicationIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-375
Number of pages6
ISBN (Electronic)9781479969340
DOIs
StatePublished - Oct 31 2014
Event2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
Duration: Sep 14 2014Sep 18 2014

Publication series

NameIEEE International Conference on Intelligent Robots and Systems
ISSN (Print)2153-0858
ISSN (Electronic)2153-0866

Other

Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
CountryUnited States
CityChicago
Period9/14/149/18/14

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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