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Title: Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements

Abstract

Applications in environmental monitoring, surveillance and patrolling typically require a network of mobile agents to collectively gain information regarding the state of a static or dynamical process evolving over a region. However, these networks of mobile agents also introduce various challenges, including intermittent observations of the dynamical process, loss of communication links due to mobility and packet drops, and the potential for malicious or faulty behavior by some of the agents. The main contribution of this paper is the development of resilient, fully-distributed, and provably correct state estimation algorithms that simultaneously account for each of the above considerations, and in turn, offer a general framework for reasoning about state estimation problems in dynamic, failure-prone and adversarial environments. Specifically, we develop a simple switched linear observer for dealing with the issue of time-varying measurement models, and resilient filtering techniques for dealing with worst-case adversarial behavior subject to time-varying communication patterns among the agents. Here, our approach considers both communication patterns that recur in a deterministic manner, and patterns that are induced by random packet drops. For each scenario, we identify conditions on the dynamical system, the patrols, the nominal communication network topology, and the failure models that guarantee applicability of ourmore » proposed techniques. Finally, we complement our theoretical results with detailed simulations that illustrate the efficacy of our algorithms in the presence of the technical challenges described above.« less

Authors:
ORCiD logo [1];  [2];  [1];  [1]
  1. Purdue Univ., West Lafayette, IN (United States). School of Electrical and Computer Engineering
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1485814
Alternate Identifier(s):
OSTI ID: 1487414
Report Number(s):
SAND-2018-3796J; SAND-2018-9348J
Journal ID: ISSN 0929-5593; 670138
Grant/Contract Number:  
AC04-94AL85000
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Autonomous Robots
Additional Journal Information:
Journal Volume: 43; Journal Issue: 3; Journal ID: ISSN 0929-5593
Publisher:
Springer
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; 42 ENGINEERING; Distributed state estimation; Byzantine attacks; Resilient robotic teams; Situational awareness

Citation Formats

Mitra, Aritra, Richards, John A., Bagchi, Saurabh, and Sundaram, Shreyas. Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements. United States: N. p., 2018. Web. doi:10.1007/s10514-018-9813-7.
Mitra, Aritra, Richards, John A., Bagchi, Saurabh, & Sundaram, Shreyas. Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements. United States. doi:10.1007/s10514-018-9813-7.
Mitra, Aritra, Richards, John A., Bagchi, Saurabh, and Sundaram, Shreyas. Wed . "Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements". United States. doi:10.1007/s10514-018-9813-7. https://www.osti.gov/servlets/purl/1485814.
@article{osti_1485814,
title = {Resilient distributed state estimation with mobile agents: overcoming Byzantine adversaries, communication losses, and intermittent measurements},
author = {Mitra, Aritra and Richards, John A. and Bagchi, Saurabh and Sundaram, Shreyas},
abstractNote = {Applications in environmental monitoring, surveillance and patrolling typically require a network of mobile agents to collectively gain information regarding the state of a static or dynamical process evolving over a region. However, these networks of mobile agents also introduce various challenges, including intermittent observations of the dynamical process, loss of communication links due to mobility and packet drops, and the potential for malicious or faulty behavior by some of the agents. The main contribution of this paper is the development of resilient, fully-distributed, and provably correct state estimation algorithms that simultaneously account for each of the above considerations, and in turn, offer a general framework for reasoning about state estimation problems in dynamic, failure-prone and adversarial environments. Specifically, we develop a simple switched linear observer for dealing with the issue of time-varying measurement models, and resilient filtering techniques for dealing with worst-case adversarial behavior subject to time-varying communication patterns among the agents. Here, our approach considers both communication patterns that recur in a deterministic manner, and patterns that are induced by random packet drops. For each scenario, we identify conditions on the dynamical system, the patrols, the nominal communication network topology, and the failure models that guarantee applicability of our proposed techniques. Finally, we complement our theoretical results with detailed simulations that illustrate the efficacy of our algorithms in the presence of the technical challenges described above.},
doi = {10.1007/s10514-018-9813-7},
journal = {Autonomous Robots},
issn = {0929-5593},
number = 3,
volume = 43,
place = {United States},
year = {2018},
month = {11}
}

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