Beyond Frontier Exploration

  • Authors:
  • Arnoud Visser; Xingrui-Ji;Merlijn Ittersum;Luis A. González Jaime;Laurenţiu A. Stancu

  • Affiliations:
  • Intelligent Systems Laboratory Amsterdam, Universiteit van Amsterdam, The Netherlands;Intelligent Systems Laboratory Amsterdam, Universiteit van Amsterdam, The Netherlands;Intelligent Systems Laboratory Amsterdam, Universiteit van Amsterdam, The Netherlands;Intelligent Systems Laboratory Amsterdam, Universiteit van Amsterdam, The Netherlands;Intelligent Systems Laboratory Amsterdam, Universiteit van Amsterdam, The Netherlands

  • Venue:
  • RoboCup 2007: Robot Soccer World Cup XI
  • Year:
  • 2008

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Abstract

This article investigates the prerequisites for a global exploration strategy in an unknown environment on a virtual disaster site. Assume that a robot equipped with a laser range scanner can build a detailed map of a previous unknown environment. The remaining question is how to use this information on this map for further exploration.On a map several interesting locations can be present where the exploration can be continued, referred as exploration frontiers. Typically, a greedy algorithm is used for the decision which frontier to explore next. Such a greedy algorithm only considers interesting locations locally, focused to reduce the movement costs. More sophisticated algorithms also take into account the information that can be gained along each frontier. This shifts the problem to estimate the amount of unexplored area behind the frontiers on the global map. Our algorithm exploits the long range of current laser scanners. Typically, during the previous exploration a small number of laser rays already passed the frontier, but this number is too low to have major impact on the generated map. Yet, the few rays through a frontier can be used to estimate the potential information gain from unexplored area beyond the frontier.