Autonomous Localization of an Unknown Number of Targets Without Data Association Using Teams of Mobile Sensors
Philip Dames, Vijay Kumar

Citation
Philip Dames, Vijay Kumar. "Autonomous Localization of an Unknown Number of Targets Without Data Association Using Teams of Mobile Sensors". IEEE Transactions on Automation Science and Engineering, 12(3), July 2015.

Abstract
This paper considers situations in which a team of mobile sensor platforms autonomously explores an environment to detect and localize an unknown number of targets. Individual sensors may be unreliable, failing to detect objects within the field of view, returning false positive measurements to clutter objects, and being unable to disambiguate true targets. In this setting, data association is difficult. We utilize the PHD filter for multi-target localization, simultaneously estimating the number of objects and their locations within the environment without the need to explicitly consider data association. Using sets of potential actions generated at multiple length scales for each robot, the team selects the joint action that maximizes the expected information gain over a finite time horizon. This is computed as the mutual information between the set of targets and the binary events of receiving no detections, effectively hedging against uninformative actions in a computationally tractable manner. We frame the controller as a receding-horizon problem. We demonstrate the real-world applicability of the proposed autonomous exploration strategy through hardware experiments, exploring an office environment with a team of ground robots. We also conduct a series of simulated experiments, varying the planning method, target cardinality, environment, and sensor modality.

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Citation formats

• HTML

  Philip Dames, Vijay Kumar. <a
  href="http://www.terraswarm.org/pubs/553.html"
  >Autonomous Localization of an Unknown Number of Targets
  Without Data Association Using Teams of Mobile
  Sensors</a>, <i>IEEE Transactions on Automation
  Science and Engineering</i>, 12(3), July 2015.

• Plain text

  Philip Dames, Vijay Kumar. "Autonomous Localization of
  an Unknown Number of Targets Without Data Association Using
  Teams of Mobile Sensors". <i>IEEE Transactions on
  Automation Science and Engineering</i>, 12(3), July
  2015.

• BibTeX

  @article{DamesKumar15_AutonomousLocalizationOfUnknownNumberOfTargetsWithout,
      author = {Philip Dames and Vijay Kumar},
      title = {Autonomous Localization of an Unknown Number of
                Targets Without Data Association Using Teams of
                Mobile Sensors},
      journal = {IEEE Transactions on Automation Science and
                Engineering},
      volume = {12},
      number = {3},
      month = {July},
      year = {2015},
      abstract = {This paper considers situations in which a team of
                mobile sensor platforms autonomously explores an
                environment to detect and localize an unknown
                number of targets. Individual sensors may be
                unreliable, failing to detect objects within the
                field of view, returning false positive
                measurements to clutter objects, and being unable
                to disambiguate true targets. In this setting,
                data association is difficult. We utilize the PHD
                filter for multi-target localization,
                simultaneously estimating the number of objects
                and their locations within the environment without
                the need to explicitly consider data association.
                Using sets of potential actions generated at
                multiple length scales for each robot, the team
                selects the joint action that maximizes the
                expected information gain over a finite time
                horizon. This is computed as the mutual
                information between the set of targets and the
                binary events of receiving no detections,
                effectively hedging against uninformative actions
                in a computationally tractable manner. We frame
                the controller as a receding-horizon problem. We
                demonstrate the real-world applicability of the
                proposed autonomous exploration strategy through
                hardware experiments, exploring an office
                environment with a team of ground robots. We also
                conduct a series of simulated experiments, varying
                the planning method, target cardinality,
                environment, and sensor modality. },
      URL = {http://terraswarm.org/pubs/553.html}
  }
  

Posted by Barb Hoversten on 5 May 2015.
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