Beyond Frontier Exploration

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.

[1]  Stefano Carpin,et al.  USARSim: Providing a Framework for Multi-Robot Performance Evaluation | NIST , 2006 .

[2]  Hans P. Moravec Sensor Fusion in Certainty Grids for Mobile Robots , 1988, AI Mag..

[3]  Héctor H. González-Baños,et al.  Navigation Strategies for Exploring Indoor Environments , 2002, Int. J. Robotics Res..

[4]  Andrew Howard,et al.  Multi-robot mapping using manifold representations , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[5]  Xingrui-Ji,et al.  Natural Boundaries , 2007 .

[6]  Stergios I. Roumeliotis,et al.  Weighted range sensor matching algorithms for mobile robot displacement estimation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[7]  Wolfram Burgard,et al.  Probabilistic Robotics (Intelligent Robotics and Autonomous Agents) , 2005 .

[8]  Ieee Robotics Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97 - Towards New Computational Principles for Robotics and Automation, July 10-11, 1997, Monterey, California, USA , 1997, CIRA.

[9]  Wolfram Burgard,et al.  Coordination for Multi-Robot Exploration and Mapping , 2000, AAAI/IAAI.

[10]  Bradley R Hasegawa Continuous observation planning for autonomous exploration , 2004 .

[11]  Brian A. Weiss,et al.  Test arenas and performance metrics for urban search and rescue robots , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[12]  Arnoud Visser,et al.  Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from RoboCup rescue , 2007, J. Field Robotics.

[13]  Wolfram Burgard,et al.  Coastal navigation-mobile robot navigation with uncertainty in dynamic environments , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[14]  Max Pfingsthorn,et al.  UvA-DARE ( Digital Academic Repository ) A scalable hybrid multi-robot SLAM method for highly detailed maps , 2007 .

[15]  Nicholas Roy,et al.  Global A-Optimal Robot Exploration in SLAM , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[16]  Hugh F. Durrant-Whyte,et al.  Coordinated search for a lost target in a Bayesian world , 2004, Adv. Robotics.

[17]  Arnoud Visser,et al.  UvA Rescue Team 2006 RoboCup Rescue - Simulation League , 2006 .

[18]  Arnoud Visser,et al.  Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from RoboCup rescue: Field Reports , 2007 .

[19]  Wolfram Burgard,et al.  Active Markov localization for mobile robots , 1998, Robotics Auton. Syst..

[20]  Brian Yamauchi,et al.  A frontier-based approach for autonomous exploration , 1997, Proceedings 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation CIRA'97. 'Towards New Computational Principles for Robotics and Automation'.