Intelligent Service Robotics

, Volume 6, Issue 4, pp 199–209 | Cite as

Local map-based exploration for mobile robots

Original Research

Abstract

For an accurate and efficient exploration, a local map-based exploration strategy is proposed. Segmented frontiers and relative transformations constitute a tree structure; using frontier segmentation and a local map management method, a robot can expand the mapped environment by moving along the tree structure. Although this local map-based exploration method uses only local maps and adjacent node information, mapping completion and efficiency can be greatly improved by merging and updating the frontier nodes. Simulation results demonstrate that the computational time does not increase during the exploration process, or when the resulting map becomes large. Additionally, the resulting path is effective in reducing the uncertainty in simultaneous localization and mapping or localization because of the loop-inducing characteristics from the child node to the parent node.

Keywords

Mobile robots Exploration Graph search Navigation 

References

  1. 1.
    Choset H, Nagatani K (2001) Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Trans Robot Autom 17(2):125–137CrossRefGoogle Scholar
  2. 2.
    Dissanayake MG, Newman P, Clark S, Durrant-Whyte HF, Csorba M (2001) A solution to the simultaneous localization and map building (SLAM) problem. IEEE Trans Robot Autom 17(3):229–241CrossRefGoogle Scholar
  3. 3.
    Montemerlo M, Thrun S, Koller D, Wegbreit B (2003) Fastslam 2.0: An improved particle filtering algorithm for simultaneous localization and mapping that provably converges. In: International Joint Conference on Artificial Intelligence, vol 18, pp 1151–1156Google Scholar
  4. 4.
    Moorehead SJ, Simmons R, Whittaker WL (2001) Autonomous exploration using multiple sources of information. In: IEEE International Conference on Robotics and Automation, vol 3, pp 3098–3103Google Scholar
  5. 5.
    Schultz AC, Adams W, Yamauchi B (1999) Integrating exploration, localization, navigation and planning with a common representation. Auton Robot 6(3):293–308CrossRefGoogle Scholar
  6. 6.
    Yamauchi B (1997) A frontier-based approach for autonomous exploration. In: IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp 146–151Google Scholar
  7. 7.
    Stachniss C, Burgard W (2003) Exploring unknown environments with mobile robots using coverage maps. In: International Joint Conference on Artificial Intelligence, vol 18, pp 1127–1134Google Scholar
  8. 8.
    Bourgault F, Makarenko AA, Williams SB, Grocholsky B, Durrant-Whyte HF (2002) Information based adaptive robotic exploration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 540–545Google Scholar
  9. 9.
    Makarenko AA, Williams SB, Bourgault F, Durrant-Whyte HF (2002) An experiment in integrated exploration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 534–539Google Scholar
  10. 10.
    Stachniss C, Grisetti G, Burgard W (2005) Information gain-based exploration using rao-blackwellized particle filters. In: Robotics: science and systems (RSS), pp 65–72Google Scholar
  11. 11.
    Sim R, Roy N (2005) Global a-optimal robot exploration in slam. In: IEEE International Conference on Robotics and Automation, pp 661–666Google Scholar
  12. 12.
    Piniés P, Tardós JD (2008) Large-scale slam building conditionally independent local maps: application to monocular vision. IEEE Trans Robot 24(5):1094–1106CrossRefGoogle Scholar
  13. 13.
    Tardós JD, Neira J, Newman PM, Leonard JJ (2002) Robust mapping and localization in indoor environments using sonar data. Int J Robot Res 21(4):311–330CrossRefGoogle Scholar
  14. 14.
    Estrada C, Neira J, Tardós JD (2005) Hierarchical slam: real-time accurate mapping of large environments. IEEE Trans Robot 21(4):588–596CrossRefGoogle Scholar
  15. 15.
    Ahn S, Choi J, Doh NL, Chung WK (2008) A practical approach for EKF-slam in an indoor environment: fusing ultrasonic sensors and stereo camera. Auton Robot 24(3):315–335 CrossRefGoogle Scholar
  16. 16.
    Blanco JL, Fernández-Madrigal JA, Gonzalez J (2007) A new approach for large-scale localization and mapping: hybrid metric-topological slam. In: IEEE International Conference on Robotics and Automation, pp 2061–2067Google Scholar
  17. 17.
    Paul R, Newman P (2010) Fab-map 3D: topological mapping with spatial and visual appearance. In: IEEE International Conference on Robotics and Automation, pp 2649–2656Google Scholar
  18. 18.
    Cummins M, Newman P (2009) Highly scalable appearance-only slam-fab-map 2.0. In: Proceedings of Robotics: Science and Systems (RSS), vol 5Google Scholar
  19. 19.
    Maddern W, Milford M, Wyeth G (2011) Continuous appearance-based trajectory SLAM. In: IEEE International Conference on Robotics and Automation, pp 3595–3600Google Scholar
  20. 20.
    Werner F, Sitte J, Maire F (2012) Topological map induction using neighbourhood information of places. Auton Robot 32(4):405–418CrossRefGoogle Scholar
  21. 21.
    Fox D, Burgard W, Thrun S (1998) Active Markov localization for mobile robots. Robot Auton Syst 25(3):195–207CrossRefGoogle Scholar
  22. 22.
    Kümmerle R, Triebel R, Pfaff P, Burgard W (2008) Monte carlo localization in outdoor terrains using multilevel surface maps. J Field Robot 25(6–7):346–359CrossRefMATHGoogle Scholar
  23. 23.
    Khalvati K, Mackworth AK (2012) Active robot localization with macro actions. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 187–193Google Scholar
  24. 24.
    Yi C, Suh IH, Lim GH, Choi BU (2009) Active-semantic localization with a single consumer-grade camera. In: IEEE International Conference on Systems, Man and Cybernetics, pp 2161–2166Google Scholar
  25. 25.
    Bailey T, Nieto J, Guivant J, Stevens M, Nebot E (2006) Consistency of the EKF-slam algorithm. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp 3562–3568Google Scholar
  26. 26.
    Dechter R, Pearl J (1985) Generalized best-first search strategies and the optimality of A*. JACM 32(3):505–536MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Robotics Laboratory, Department of Mechanical EngineeringPohang University of Science and Technology (POSTECH)PohangKorea

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