Skip to main content

Autonomous Indoor Mobile Robot Exploration Based on Wavefront Algorithm

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11744))

Abstract

Autonomous’ exploration is an important part of mobile robots. In an unknown environment, if a mobile robot wants to complete a task, the robot must be able to explore the environment. This paper proposes a new exploration strategy based on the wavefront algorithm. The wavefront algorithm is used to find the closest frontier point in very short time for the mobile robot. After determining the next frontier point, the mobile robot moves to the frontier point according to the path planned by the wavefront algorithm, which is the shortest. The exploration task is completed when there are no frontier points in the map. Finally, the exploration strategy is tested using the Robot Operating System (ROS). Simulation experiments show that the exploration based on the wavefront algorithm can find the frontier points rapidly and ensure the integrity of the exploration environment.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Yamauchi, B.: A frontier-based approach for autonomous exploration. In: 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 146–151, IEEE (1997)

    Google Scholar 

  2. Gonzalez-Banos, H.H., Latombe, J.C.: Navigation strategies for exploring indoor environments. Int. J. Robot. Res. 21, 829–848 (2002)

    Article  Google Scholar 

  3. Vallve, J., Andrade-Cetto, J.: Mobile robot exploration with potential information fields. In: European Conference on Mobile Robots, pp. 222–227 (2013)

    Google Scholar 

  4. Bai, S., Wang, J., Chen, F., Englot, B.: Information-theoretic exploration with Bayesian optimization. In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1816–1822. IEEE (2016)

    Google Scholar 

  5. Umari, H., Mukhopadhyay, S.: Autonomous robotic exploration based on multiple rapidly-exploring randomized trees. In: 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1396–1402. IEEE (2017)

    Google Scholar 

  6. Lavalle, S.M.: Rapidly-exploring random trees: a new tool for path planning (1999)

    Google Scholar 

  7. LaValle, S.M., Kuffner, J.J.: Randomized kinodynamic planning. Int. J. Robot. Res. 20, 378–400 (2016)

    Article  Google Scholar 

  8. Moravec, H., Elfes, A.: High resolution maps from wide angle sonar. In: 1985 IEEE Conference on Robotics and Automation, pp. 116–121. IEEE (1985)

    Google Scholar 

  9. Grisetti, G., Stachniss, C., Burgard, W.: Improving grid-based SLAM with Rao-Blackwellized particle filters by adaptive proposals and selective resampling. In: 2005 IEEE International Conference on Robotics and Automation. IEEE (2005)

    Google Scholar 

  10. Grisetti, G., Stachniss, C., Burgard, W.: Improved techniques for grid mapping with Rao-Blackwellized particle filters. In: 2007 IEEE Transactions on Robotics, pp. 34–46. IEEE (2007)

    Article  Google Scholar 

  11. Smith, R., Self, M., Cheeseman, P.: Estimating uncertain spatial relationships in robotics. In: Cox, I.J., Wilfong, G.T. (eds.) Autonomous Robot Vehicles, pp. 167–193. Springer, New York (1990). https://doi.org/10.1007/978-1-4613-8997-2_14

    Chapter  Google Scholar 

  12. Gmapping ROS package.Internet. http://wiki.ros.org/gmapping

  13. Move_base ROS package.Internet. http://wiki.ros.org/move_base

  14. Gazebo simulator.Internet. http://gazebosim.org/. http://wiki.ros.org/move_base14.Gazebosimulator.Internet

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rongchuan Sun .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Tang, C., Sun, R., Yu, S., Chen, L., Zheng, J. (2019). Autonomous Indoor Mobile Robot Exploration Based on Wavefront Algorithm. In: Yu, H., Liu, J., Liu, L., Ju, Z., Liu, Y., Zhou, D. (eds) Intelligent Robotics and Applications. ICIRA 2019. Lecture Notes in Computer Science(), vol 11744. Springer, Cham. https://doi.org/10.1007/978-3-030-27541-9_28

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-27541-9_28

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-27540-2

  • Online ISBN: 978-3-030-27541-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics