Skip to main content
SpringerLink
Log in

Scan matching online cell decomposition for coverage path planning in an unknown environment

  • Published:
International Journal of Precision Engineering and Manufacturing Aims and scope Submit manuscript

Abstract

This paper presents a novel sensor-based online coverage path-planning algorithm that guarantees the complete coverage of an unknown rectilinear workspace for the task of a mobile robot. The proposed algorithm divides the workspace of the robot into cells at each scan sample. This division can be classified as an exact cell decomposition method, which incrementally constructs cell decomposition while the robot covers an unknown workspace. To guarantee complete coverage, a closed map representation based on a feature extraction that consists of a set of line segments called critical edges is proposed. In this algorithm, cell boundaries are formed by extended critical edges, which are the sensed partial contours of walls and objects in the workspace. The robot uses a laser scanner to sense the critical edges. Sensor measurement is sampled twice in each cell. Scan matching is performed to merge map information between the reference scan and the current scan. At each scan sample, a two-direction oriented rectilinear decomposition is achieved in the workspace and presented by a closed map representation. The construction order of the cells is very important in this incremental cell decomposition algorithm. To choose the next target cell from candidate cells, the robot checks for redundancy in the planned path and for possible positions of the ending points of the current cell. The key point of the algorithm is memorizing the covered space to define the next target cell from possible cells. The path generation within the defined cell is determined to minimize the number of turns, which is the main factor in saving time during the coverage. Therefore, the cell’s long boundary should be chosen as the main path of the robot. This algorithm is verified by an experiment under the LABVIEW environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Latombe, J. C., “Robot motion planning,” Kluwer Academic Publishers, 1991.

    Book  Google Scholar 

  2. Choset, H., “Coverage of known space: the boustrophedon cellular decomposition,” Autonomous Robots, Vol. 9, No. 3, pp. 247–253, 2000.

    Article  Google Scholar 

  3. Acar, E., Choset, H., Rizzi, A. A., Atkar, P. N., and Hull, D., “Morse decompositions for the coverage task,” Int. J. of Robotics Research, Vol. 21, pp. 331–344, 2002.

    Article  Google Scholar 

  4. Janchiv, A., Batsaikhan, D., Kim, B. S., Lee, W. G., and Lee, S. G., “Time-efficient and complete coverage path planning based on flow networks for multi-robots,” International Journal of Control, Automation and Systems, Vol. 11, No. 2, pp. 369–376, 2013.

    Article  Google Scholar 

  5. Choset, H., Acar, E., Rizzi, A. A., and Luntz, J., “Exact cellular decompositions in terms of critical points of morse functions,” Proc. IEEE International Conference on Robotics and Automation, Vol. 3, pp. 2270–2277, 2000.

    Google Scholar 

  6. Acar, E. U. and Choset, H., “Robust sensor-based coverage of unstructured environment,” Proc. IEEE International Conference on Intelligent Robots and Systems, Vol. 1, pp. 61–68, 2001.

    Google Scholar 

  7. Acar, E. and Choset, H., “Sensor-based coverage of unknown environments: incremental construction of Morse decompositions,” Int. J. Robotics Research, Vol. 21, pp. 345–366, 2002.

    Article  Google Scholar 

  8. Choset, H. and Burdick, J., “Sensor-based motion planning: incremental construction of the hierarchical generalized Voronoi graph,” Int. J. of Robotics Research, Vol. 19, No. 2, pp. 126–148, 2000.

    Article  Google Scholar 

  9. Acar, E., Choset, H., and Lee, J. Y., “Sensor-based coverage with extended range detectors,” IEEE Transactions on Robotics, Vol. 22, No. 1, 2006.

    Google Scholar 

  10. Gabriely, Y. and Rimon, E., “Spiral-STC: an on-line coverage algorithm of grid environments by a mobile robot,” Proc. IEEE International Conference on Robotics and Automation, Vol. 1, pp. 954–960, 2002.

    Google Scholar 

  11. Gonzalez, E., Alvarez, O., Diaz, Y., Parra, C., and Bustacara, C., “BSA: A Complete Coverage Algorithm,” Proc. IEEE International Conference on Robotics and Automation, pp. 2040–2044, 2005.

    Google Scholar 

  12. Choi, Y. H., Lee, T. K., Baek, S., and Oh, S. Y., “Online complete coverage path planning for mobile robots based on linked spiral paths using constrained inverse distance transform,” Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 5788–5793, 2009.

    Google Scholar 

  13. Lee, T. K., Baek, S. H, Choi, Y. H., and Oh, S. Y., “Smooth coverage path planning and control of mobile robots based on highresolution grid map representation,” Int. J. Robotics and Autonomous Systems, Vol. 59, pp. 801–812, 2011.

    Article  Google Scholar 

  14. Lee, T. K., Baek, S. H., and Oh, S. Y., “Sector-based maximal online coverage of unknown environments for cleaning robots with limited sensing,” Int. J. of Robotics and Autonomous Systems, Vol. 59, No. 10, pp. 698–710, 2011.

    Article  Google Scholar 

  15. Myung, H., Jeon, H. M., and Jeong, W. Y., “Virtual door algorithm for coverage path planning of mobile robot,” Proc. IEEE International Symposium on Industrial Electronics, pp. 658–663, 2009.

    Google Scholar 

  16. Hara, Y., Kawata, H., Ohya, A., and Yuta, S., “Map building for mobile robots using a SOKUIKI sensor robust scan matching using laser reflection intensity,” Int Joint Conf. on SICE-ICASE, pp. 5951–5956, 2006.

    Google Scholar 

  17. Lee, H. C., Lee, S. H., Lee, S. H., Lee, T. S., Kim, D. J., Park, K. S., Lee, K. W., and Lee, B. H., “Comparison and analysis of scan matching techniques for cooperative-SLAM,” Int. Conf. on Ubiquitous Robots and Ambient Intelligence, pp. 165–168, 2011.

    Google Scholar 

  18. Diosi, A. and Kleeman, L., “Laser Scan Matching in Polar Coordinates with Application to SLAM,” IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3317–3322, 2005.

    Google Scholar 

  19. Chang, H. J., Lee, C. S. G., Lu, Y. H., and Hu, Y. C., “P-SLAM: Simultaneous Localization and Mapping With Environmental Structure Prediction,” IEEE Transactions on Robotics, Vol. 23, No. 2, pp. 281–293, 2007.

    Article  Google Scholar 

  20. Nguyen, V., Harati, A., Martinelli, A., Tomatis, N., and Sa, B., “Orthogonal SLAM: a step toward lightweight indoor autonomous navigation,” Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006.

    Google Scholar 

  21. Saitov, D. and Lee, S. G., “Mobile robot navigation based on EWA with adaption of particle filter and map merging algorithms for localization and mapping,” Int. J. Precis. Eng. Manuf., Vol. 12, No. 3, pp. 451–459, 2011

    Article  Google Scholar 

  22. Batsaikhan, D., Janchiv, A., and Lee, S. G., “Sensor-Based Incremental Boustrophedon Decomposition for Coverage Path Planning of a Mobile Robot, in: Lee, S., Cho, H., Yoon, K. J., and Lee, J. (Eds.), Intelligent Autonomous Systems 12,” Springer, Vol. 193, pp. 621–628, 2013.

    Article  Google Scholar 

  23. Censi, A., Iocchi, L., and Grisetti, G., “Scan matching in the Hough domain,” Proc. IEEE International Conference on Robotics and Automation, pp. 2739–2744, 2005.

    Google Scholar 

  24. Nguyen, V., Martinelli, A., Tomatis, N., and Siegwart, R., “A comparison of line extraction algorithms using 2D laser range finder for indoor mobile robotics,” Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1929–1934, 2005.

    Google Scholar 

  25. Baek, S., Lee, T. K., OH, S. Y., and Ju, K., “Integrated On-Line Localization, Mapping and Coverage Algorithm of Unknown Environments for Robotic Vacuum Cleaners Based on Minimal Sensing,” Advanced Robotics, Vol. 25, pp. 1651–1673, 2011.

    Article  Google Scholar 

  26. Butler, Z. J., Rizzi, A. A., and Hollis, R. L., “Cooperative coverage of rectilinear environments,” Proc. IEEE International Conference on Robotics and Automation, Vol. 3, pp. 2722–2727, 2000.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechanical Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin, 446-701, South Korea

    Batsaikhan Dugarjav, Soon-Geul Lee & Nak Young Chong

  2. School of Electronic Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin, 446-701, South Korea

    Donghan Kim

  3. Dept. of Mechanical System Design Eng., Seoul National University of Science & Technology, Gongneung-dong, Nowon-ku, Seoul, 139-743, South Korea

    Jong Hyeong Kim

  4. School of Information Science, Japan Advanced Institute of Science and Technology, Asahidai, Nomi, Ishikawa, 923-1292, Japan

    Nak Young Chong

Authors
  1. Batsaikhan Dugarjav
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Soon-Geul Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Donghan Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jong Hyeong Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Nak Young Chong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Soon-Geul Lee.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dugarjav, B., Lee, SG., Kim, D. et al. Scan matching online cell decomposition for coverage path planning in an unknown environment. Int. J. Precis. Eng. Manuf. 14, 1551–1558 (2013). https://doi.org/10.1007/s12541-013-0209-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12541-013-0209-5

Keywords

Search

Navigation