Multi-Robot Target Search using Probabilistic Consensus on Discrete Markov Chains

Aniket Shirsat, Karthik Elamvazhuthi, Spring Berman

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

1 Scopus citations

Abstract

In this paper, we propose a probabilistic consensus-based multi-robot search strategy that is robust to communication link failures, and thus is suitable for disaster affected areas. The robots, capable of only local communication, explore a bounded environment according to a random walk modeled by a discrete-time discrete-state (DTDS) Markov chain and exchange information with neighboring robots, resulting in a time-varying communication network topology. The proposed strategy is proved to achieve consensus, here defined as agreement on the presence of a static target, with no assumptions on the connectivity of the communication network. Using numerical simulations, we investigate the effect of the robot population size, domain size, and information uncertainty on the consensus time statistics under this scheme. We also validate our theoretical results with 3D physics-based simulations in Gazebo. The simulations demonstrate that all robots achieve consensus in finite time with the proposed search strategy over a range of robot densities in the environment.

Original languageEnglish (US)
Title of host publication2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020
EditorsLino Marques, Majid Khonji, Jorge Dias
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages108-115
Number of pages8
ISBN (Electronic)9781665403900
DOIs
StatePublished - Nov 4 2020
Event2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020 - Abu Dhabi, United Arab Emirates
Duration: Nov 4 2020Nov 6 2020

Publication series

Name2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020

Conference

Conference2020 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2020
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Period11/4/2011/6/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Safety Research

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