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Taking Turns in Complete Coverage for Multiple Robots

  • Lee-or AlonEmail author
  • Noa Agmon
  • Gal A. Kaminka
Conference paper
Part of the Springer Proceedings in Advanced Robotics book series (SPAR, volume 9)

Abstract

Coverage is a canonical task where a robot or a group of robots are required to visit every point in a given work area, typically within the shortest possible time. Previous work on offline coverage highlighted the benefits of determining a circular coverage path, divided into segments for different robots (if more than one). This paper contributes a number of significant improvements to the planning and utilization of circular coverage paths with single and multiple robots. We focus on circular paths that exactly decompose the environment into cells, where each obstacle-free cell is covered in a back-and-forth movement. We show that locally changing the coverage direction (alignment) in each cell can improve coverage time, and that this allows for merging bordering cells into larger cells, significantly reducing the number of turns taken by the robots. We additionally present a novel data structure to compactly represent all possible coverage and non-coverage paths between cells in the work area. Finally, we discuss the complexity of global multi-robot assignment of path segments, and present greedy polynomial-time approximations which provide excellent results in practice.

Keywords

Multi-robot systems Coverage 

Notes

Acknowledgements

This research was supported by ISF grant #2306/18. As always, thanks to K. Ushi.

References

  1. 1.
    Agmon, N., Hazon, N., Kaminka, G.A.: The giving tree: constructing trees for efficient offline and online multi-robot coverage. Ann. Math. Artif. Intell. 52(2–4), 143–168 (2008)MathSciNetCrossRefGoogle Scholar
  2. 2.
    Choset, H., Pignon, P.: Coverage Path Planning: The Boustrophedon Decomposition. Australia, Canberra (1997)Google Scholar
  3. 3.
    Coppersmith, D., Winograd, S.: Matrix multiplication via arithmetic progressions. J. Symb. Comput. 9(3), 251–280 (1987)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to Algorithms. MIT Press, Cambridge (1990)Google Scholar
  5. 5.
    Gabriely, Y., Rimon, E.: Spanning-tree based coverage of continuous areas by a mobile robot. Ann. Math. Artif. Intell. 31(1–4), 77–98 (2001)CrossRefGoogle Scholar
  6. 6.
    Gage, D.W.: Command control for many-robot systems. In: The nineteenth annual AUVS Technical Symposium (AUVS-92) (1992)Google Scholar
  7. 7.
    Galceran, E., Carreras, M.: A survey on coverage path planning for robotics. Robot. Auton. Syst. 61(12), 1258–1276 (2013). http://www.sciencedirect.com/science/article/pii/S092188901300167XCrossRefGoogle Scholar
  8. 8.
    Guan, M.K.: Graphic programming using odd or even points. Chin. Math. 1(3), 273–277 (1962)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Hazon, N., Kaminka, G.: On redundancy, efficiency, and robustness in coverage for multiple robots. Robot. Auton. Syst. 56(12), 1102–1114 (2008)CrossRefGoogle Scholar
  10. 10.
    Huang, W.H.: Optimal line-sweep-based decompositions for coverage algorithms. In: Proceedings the IEEE International Conference on Robotics and Automation, pp. 27–32 (2001)Google Scholar
  11. 11.
    Karapetyan, N., Benson, K., McKinney, C., Taslakian, P., Rekleitis, I.: Efficient multi-robot coverage of a known environment. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 1846–1852 (2017)Google Scholar
  12. 12.
    Lumelsky, V.J., Mukhopadhyay, S., Sun, K.: Dynamic path planning in sensor-based terrain acquisition. IEEE Trans. Robot. Autom. 6(4), 462–472 (1990)CrossRefGoogle Scholar
  13. 13.
    Rekleitis, I., New, A., E.S.R., Choset, H.,: Efficient boustrophedon multi-robot coverage: an algorithmic approach. Ann. Math. Artif. Intell. 52(2–4), 109–142 (2008)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Xu, A., Viriyasuthee, C., Rekleitis, I.: Efficient complete coverage of a known arbitrary environment with applications to aerial operations. Auton. Robot. 36(4), 365–381 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Bar-Ilan UniversityRamat GanIsrael

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