Information Theoretic Multi-Target Localization with Robot Swarms
Philip Dames, Vijay Kumar

Citation
Philip Dames, Vijay Kumar. "Information Theoretic Multi-Target Localization with Robot Swarms". Talk or presentation, 5, November, 2013; Poster presented at the 2013 TerraSwarm Annual Meeting.

Abstract
This work addresses the task of searching for an unknown number of targets within a known obstacle map using a team of mobile robots equipped with noisy, limited field-of-view sensors. Such sensors may fail to detect a subset of the visible targets or return false positive detections. These measurement sets are used to localize the target set using the Probability Hypothesis Density, or PHD, filter. Robots communicate with each other on a local peer-to-peer basis and with a server or the cloud via access points, exchanging measurements to update their belief about the target set and poses to plan future actions. The server provides a mechanism to collect and synthesize information from all robots and to share the global, albeit time-delayed, belief state to robots near access points. We design a decentralized control scheme for the robots that exploits this architecture, the robot-to-robot and robot-to-server communication links, and the PHD representation of the belief state. Specifically, robots move in such a way as to maximize mutual information between the target set and measurements, both self-collected and those available by accessing the server, balancing local exploration with sharing knowledge across the team, using a finite state machine to switch between these actions. Furthermore, robots coordinate their actions with other robots exploring the same local region of the environment.

Electronic downloads

Internal. This publication has been marked by the author for TerraSwarm-only distribution, so electronic downloads are not available without logging in.

Citation formats

• HTML

  Philip Dames, Vijay Kumar. <a
  href="http://www.terraswarm.org/pubs/163.html"><i>Information
  Theoretic Multi-Target Localization with Robot
  Swarms</i></a>, Talk or presentation,  5,
  November, 2013; Poster presented at the <a
  href="http://www.terraswarm.org/conferences/13/annual"
  >2013 TerraSwarm Annual Meeting</a>.

• Plain text

  Philip Dames, Vijay Kumar. "Information Theoretic
  Multi-Target Localization with Robot Swarms". Talk or
  presentation,  5, November, 2013; Poster presented at the
  <a
  href="http://www.terraswarm.org/conferences/13/annual"
  >2013 TerraSwarm Annual Meeting</a>.

• BibTeX

  @presentation{DamesKumar13_InformationTheoreticMultiTargetLocalizationWithRobot,
      author = {Philip Dames and Vijay Kumar},
      title = {Information Theoretic Multi-Target Localization
                with Robot Swarms},
      day = {5},
      month = {November},
      year = {2013},
      note = {Poster presented at the <a
                href="http://www.terraswarm.org/conferences/13/annual"
                >2013 TerraSwarm Annual Meeting</a>.},
      abstract = {This work addresses the task of searching for an
                unknown number of targets within a known obstacle
                map using a team of mobile robots equipped with
                noisy, limited field-of-view sensors. Such sensors
                may fail to detect a subset of the visible targets
                or return false positive detections. These
                measurement sets are used to localize the target
                set using the Probability Hypothesis Density, or
                PHD, filter. Robots communicate with each other on
                a local peer-to-peer basis and with a server or
                the cloud via access points, exchanging
                measurements to update their belief about the
                target set and poses to plan future actions. The
                server provides a mechanism to collect and
                synthesize information from all robots and to
                share the global, albeit time-delayed, belief
                state to robots near access points. We design a
                decentralized control scheme for the robots that
                exploits this architecture, the robot-to-robot and
                robot-to-server communication links, and the PHD
                representation of the belief state. Specifically,
                robots move in such a way as to maximize mutual
                information between the target set and
                measurements, both self-collected and those
                available by accessing the server, balancing local
                exploration with sharing knowledge across the
                team, using a finite state machine to switch
                between these actions. Furthermore, robots
                coordinate their actions with other robots
                exploring the same local region of the environment.},
      URL = {http://terraswarm.org/pubs/163.html}
  }
  

Posted by Philip Dames on 3 Nov 2013.