Mobile Wireless Network Infrastructure on Demand

Daniel Mox, Miguel Calvo-Fullana, Mikhail Gerasimenko, Jonathan Fink, Vijay Kumar, Alejandro Ribeiro

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)


In this work, we introduce Mobile Wireless Infrastructure on Demand: a framework for providing wireless connectivity to multi-robot teams via autonomously reconfiguring ad-hoc networks. In many cases, previous multi-agent systems either assumed the availability of existing communication infrastructure or were required to create a network in addition to completing their objective. Instead our system explicitly assumes the responsibility of creating and sustaining a wireless network capable of satisfying end-to-end communication requirements of a team of agents, called the task team, performing an arbitrary objective. To accomplish this goal, we propose a joint optimization framework that alternates between finding optimal network routes to support data flows between the task agents and improving the performance of the network by repositioning a collection of mobile relay nodes referred to as the network team. We demonstrate our approach with simulations and experiments wherein wireless connectivity is provided to patrolling task agents.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation, ICRA 2020
Number of pages7
ISBN (Electronic)9781728173955
Publication statusPublished - May 2020
Publication typeA4 Article in conference proceedings
EventIEEE International Conference on Robotics and Automation - Paris, France
Duration: 31 May 202031 Aug 2020

Publication series

Name IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729
ISSN (Electronic)2379-9552


ConferenceIEEE International Conference on Robotics and Automation

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

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


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