Distributed Autonomous Robotic Systems pp 401-412 | Cite as
Taking Turns in Complete Coverage for Multiple Robots
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 CoverageNotes
Acknowledgements
This research was supported by ISF grant #2306/18. As always, thanks to K. Ushi.
References
- 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.Choset, H., Pignon, P.: Coverage Path Planning: The Boustrophedon Decomposition. Australia, Canberra (1997)Google Scholar
- 3.Coppersmith, D., Winograd, S.: Matrix multiplication via arithmetic progressions. J. Symb. Comput. 9(3), 251–280 (1987)MathSciNetCrossRefGoogle Scholar
- 4.Cormen, T.H., Leiserson, C.E., Rivest, R.L.: Introduction to Algorithms. MIT Press, Cambridge (1990)Google Scholar
- 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.Gage, D.W.: Command control for many-robot systems. In: The nineteenth annual AUVS Technical Symposium (AUVS-92) (1992)Google Scholar
- 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.Guan, M.K.: Graphic programming using odd or even points. Chin. Math. 1(3), 273–277 (1962)MathSciNetzbMATHGoogle Scholar
- 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.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.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.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.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.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