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Multi-robot repeated area coverage

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Abstract

We address the problem of repeated coverage of a target area, of any polygonal shape, by a team of robots having a limited visual range. Three distributed Cluster-based algorithms, and a method called Cyclic Coverage are introduced for the problem. The goal is to evaluate the performance of the repeated coverage algorithms under the effects of the variables: Environment Representation, and the Robots’ Visual Range. A comprehensive set of performance metrics are considered, including the distance the robots travel, the frequency of visiting points in the target area, and the degree of balance in workload distribution among the robots. The Cyclic Coverage approach, used as a benchmark to compare the algorithms, produces optimal or near-optimal solutions for the single robot case under some criteria. The results can be used as a framework for choosing an appropriate combination of repeated coverage algorithm, environment representation, and the robots’ visual range based on the particular scenario and the metric to be optimized.

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Notes

  1. In this paper, we use the terms ’coverage’ and ’repeated coverage’ interchangeably.

  2. All figures in this paper are best viewed in color.

References

  • Agmon, N., Hazon, N., & Kaminka, G. A. (2008a). The giving tree: Constructing trees for efficient offline and online multi-robot coverage. Annals of Mathematics and Artificial Intelligence, 52(2–4), 143–168.

    Article  MATH  MathSciNet  Google Scholar 

  • Agmon, N., Kraus, S., & Kaminka, G. (2008b). Multi-robot perimeter patrol in adversarial settings. In Proceedings of the IEEE international conference on robotics and automation, ICRA 2008 (pp. 2339–2345).

  • Agmon, N., Kraus, S., & Kaminka, G. A. (2009a). Uncertainties in adversarial patrol. In Proceedings of the 8th international conference on autonomous agents and multiagent systems, AAMAS ’09 (Vol. 2, pp. 1267–1268).

  • Agmon, N., Kraus, S., Kaminka, G. A., & Sadov, V. (2009b). Adversarial uncertainty in multi-robot patrol. In Proceedings of the 21st international joint conference on artificial intelligence, IJCAI’09 (pp. 1811–1817).

  • Agmon, N., Sadov, V., Kaminka, G., & Kraus, S. (2008c). The impact of adversarial knowledge on adversarial planning in perimeter patrol. In Proceedings of the 7th international joint conference on autonomous agents and multiagent systems (Vol. 1, pp. 55–62). Japan: International Foundation for Autonomous Agents and Multiagent Systems.

  • Ahmadi, M., & Stone, P. (2006). A multi-robot system for continuous area sweeping tasks. In Proceedings of the IEEE international conference on robotics and automation, ICRA 2006 (pp. 1724–1729).

  • Almeida, A., Ramalho, G., Santana, H., Tedesco, P. A., Menezes, T., Corruble, V., et al. (2004). Recent advances on multi-agent patrolling. In Proceedings of the Brazilian symposium on artificial intelligence, SBIA 2004 (pp. 474–483).

  • Amstutz, P., Correll, N., & Martinoli, A. (2008). Distributed boundary coverage with a team of networked miniature robots using a robust market-based algorithm. Annals Mathematics Artificial Intelligence, 52(2–4), 307–333.

    Article  MATH  MathSciNet  Google Scholar 

  • Applegate, D., Cook, W., & Rohe, A. (2003). Chained Lin-Kernighan for large traveling salesman problems. INFORMS Journal on Computing, 15, 82–92.

    Article  MATH  MathSciNet  Google Scholar 

  • Applegate, D. L., Bixby, R. E., Chvatal, V., & Cook, W. J. (2007). The traveling salesman problem: A computational Study. Princeton, NJ: Princeton University Press.

  • Batalin, M. A., & Sukhatme, G. S. (2002). Spreading out: A local approach to multi-robot coverage. In Proceedings of 6th international symposium on distributed autonomous robotic systems, DARS 2002 (pp. 373–382).

  • Batalin, M., & Sukhatme, G. (2003). Efficient exploration without localization. In Proceedings of the IEEE international conference on robotics and automation, ICRA 2003 (Vol. 2, pp. 2714–2719).

  • Boardman, M., Edmonds, J., Francis, K., & Clark, C. (2010). Multi-robot boundary tracking with phase and workload balancing. In IEEE/RSJ international conference on intelligent robots and systems, IROS 2010 (pp. 3321–3326).

  • Burgard, W., Moors, M., Fox, D., Simmons, R., & Thrun, S. (2000). Collaborative multi-robot exploration. In Proceedings of the IEEE international conference on robotics and automation, ICRA 2000 (pp. 476–481).

  • Carlsson, S., Jonsson, H., & Nilsson, B. J. (1999). Finding the shortest watchman route in a simple polygon. Discrete and Computational Geometry, 22, 377–402.

    Article  MATH  MathSciNet  Google Scholar 

  • Carlsson, S., Nilsson, B. J., & Ntafos, S. C. (1993). Optimum guard covers and m-watchmen routes for restricted polygons. International Journal of Computational Geometry and Applications, 3(1), 85–105.

    Article  MATH  MathSciNet  Google Scholar 

  • Chandra, B., Karloff, H., & Tovey, C. (1999). New results on the old k-opt algorithm for the traveling salesman problem. SIAM Journal on Computing, 28, 1998–2029.

    Article  MATH  MathSciNet  Google Scholar 

  • Chew, L. P. (1987). Constrained delaunay triangulations. In Proceedings of the symposium on computational geometry, SCG (pp. 215–222).

  • Chin, W., & Ntafos, S. (1986). Optimum watchman routes. In Proceedings of the second annual symposium on computational geometry, SCG 1986 (pp. 24–33). New York, NY: ACM.

  • Choset, H. (2001). Coverage for robotics—a survey of recent results. Annals of Mathematics and Artificial Intelligence, 31(1–4), 113–126.

    Article  Google Scholar 

  • Czyzowicz, J., Gasieniec, L., Kosowski, A., & Kranakis, E. (2011). Boundary patrolling by mobile agents with distinct maximal speeds. In Proceedings of the 19th European conference on algorithms, ESA 2011 (pp. 701–712).

  • De Berg, M., Cheong, O., Van Kreveld, M., & Overmars, M. (2008). Computational geometry: Algorithms and applications. New York: Springer.

    MATH  Google Scholar 

  • Desrochers, M., Desrosiers, J., & Solomon, M. (1992). A new optimization algorithm for the vehicle routing problem with time windows. Operation Research, 40(2), 342–354.

    Article  MATH  MathSciNet  Google Scholar 

  • Elmaliach, Y., Agmon, N., & Kaminka, G. A. (2009). Multi-robot area patrol under frequency constraints. Annals of Mathematics and Artificial Intelligence, 57(3–4), 293–320.

    Article  MATH  MathSciNet  Google Scholar 

  • Elmaliach, Y., Shiloni, A., & Kaminka, G. A. (2008). A realistic model of frequency-based multi-robot polyline patrolling. In Proceedings of the 7th international joint conference on autonomous agents and multiagent systems, AAMAS 2008 (pp. 63–70).

  • Faigl, J. (2010). Approximate solution of the multiple watchman routes problem with restricted visibility range. IEEE Transactions on Neural Networks, 21(10), 1668–1679.

    Article  Google Scholar 

  • Faigl, J., Kulich, M., & Přeučil, L. (2011). A sensor placement algorithm for a mobile robot inspection planning. Journal of Intelligent and Robotic Systems, 62, 329–353.

    Article  Google Scholar 

  • Fazli, P., Davoodi, A., Pasquier, P., & Mackworth, A. K. (2010a). Complete and robust cooperative robot area coverage with limited range. In Proceedings of the 2010 IEEE/RSJ international conference on intelligent robots and systems, IROS 2010 (pp. 5577–5582).

  • Fazli, P., Davoodi, A., Pasquier, P., & Mackworth, A. K. (2010b). Multi-robot area coverage with limited visibility. In Proceedings of the 9th international conference on autonomous agents and multiagent systems, AAMAS 2010 (pp. 1501–1502).

  • Fazli, P., & Mackworth, A. K. (2012a). The effects of communication and visual range on multi-robot repeated boundary coverage. In proceedings of the 10th IEEE international symposium on safely, security, and rescue robotics, SSRR 2012. College Station, TX.

  • Fazli, P., & Mackworth, A. K. (2012b). Multi-robot repeated boundary coverage under uncertainty. In Proceedings of the IEEE international conference on robotics and biomimetics, ROBIO 2012. Guangzhou, China.

  • Gabriely, Y., & Rimon, E. (2001). Spanning-tree based coverage of continuous areas by a mobile robot. Annals of Mathematics and Artificial Intelligence, 31(1–4), 77–98.

    Article  Google Scholar 

  • Gasparri, A., Krishnamachari, B., & Sukhatme, G. (2008). A framework for multi-robot node coverage in sensor networks. Annals of Mathematics and Artificial Intelligence, 52(2), 281–305.

    Article  MATH  MathSciNet  Google Scholar 

  • Gerkey, B. P., Thrun, S., & Gordon, G. (2006). Visibility-based pursuit-evasion with limited field of view. International Journal of Robotics Research, 25(4), 299–315.

    Article  Google Scholar 

  • Girard, A., Howell, A., & Hedrick, J. (2004). Border patrol and surveillance missions using multiple unmanned air vehicles. In IEEE conference on decision and control, CDC 2004 (Vol. 1, pp. 620–625).

  • Guo, Y., Parker, L. E., & Madhavan, R. (2007). Collaborative robots for infrastructure security applications. In Mobile robots, studies in computational intelligence (Vol. 50, pp. 185–200). New York: Springer.

  • Hartigan, J. A., & Wong, M. A. (1979). Algorithm as 136: A k-means clustering algorithm. Journal of the Royal Statistical Society. Series C (Applied Statistics), 28(1), 100–108.

    Google Scholar 

  • Hazon, N., & Kaminka, G. A. (2008). On redundancy, efficiency, and robustness in coverage for multiple robots. Robotics and Autonomous Systems, 56(12), 1102–1114.

    Article  Google Scholar 

  • Helsgaun, K. (2009). General k-opt submoves for the Lin-Kernighan TSP heuristic. Mathematical Programming Computation, 1(2), 119–163.

    Article  MATH  MathSciNet  Google Scholar 

  • Hofner, C., & Schmidt, G. (1994). Path planning and guidance techniques for an autonomous mobile cleaning robot. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, IROS 1994 (pp. 610–617).

  • Hoos, H., & Sttzle, T. (2004). Stochastic local search: Foundations applications. San Francisco: Morgan Kaufmann.

    Google Scholar 

  • Howard, A. (2006). Multi-robot simultaneous localization and mapping using particle filters. International Journal of Robotics Research, 25(12), 1243–1256.

    Article  Google Scholar 

  • Jennings, J., Whelan, G., & Evans, W. (1997). Cooperative search and rescue with a team of mobile robots. In Proceedings of 8th international conference on advanced robotics, ICAR 1997 (pp. 193–200).

  • Jensen, E., Franklin, M., Lahr, S., & Gini, M. (2011). Sustainable multi-robot patrol of an open polyline. In Proceedings of the IEEE international conference on robotics and automation (pp. 4792–4797).

  • Kazazakis, G. D., & Argyros, A. A. (2002). Fast positioning of limited visibility guards for inspection of 2D workspaces. In Proceedings of the 2002 IEEE/RSJ international conference on intelligent robots and systems, IROS 2002 (pp. 2843–2848).

  • Kurabayashi, D., Ota, J., Arai, T., Ichikawa, S., Koga, S., Asama, H. et al. (1996). Cooperative sweeping by multiple mobile robots with relocating portable obstacles. In Proceedings of the 1996 IEEE/RSJ international conference on intelligent robots and systems, IROS 1996 (Vol. 3, pp. 1472–1477).

  • Latombe, J. C. (1991). Robot motion planning. Norwell: Kluwer.

    Book  Google Scholar 

  • LaValle, S., & Hinrichsen, J. (2001). Visibility-based pursuit-evasion: The case of curved environments. IEEE Transactions on Robotics and Automation, 17(2), 196–202.

    Article  Google Scholar 

  • Lavalle, S. M., Lin, D., Guibas, L. J., Claude Latombe, J., & Motwani, R. (1997). Finding an unpredictable target in a workspace with obstacles. In Proceedings of the IEEE international conference on robotics and automation, ICRA 1997 (pp. 737–742).

  • Lee, D. T., & Schachter, B. J. (1980). Two algorithms for constructing a delaunay triangulation. International Journal of Computer Information Science, 9(3), 219–242.

    Article  MATH  MathSciNet  Google Scholar 

  • Lin, S., & Kernighan, B. (1973). An effective heuristic algorithm for the traveling-salesman problem. Operations Research, 21(2), 498–516.

    Article  MATH  MathSciNet  Google Scholar 

  • Liu, F., & Shen, S. (1999). A method for vehicle routing problem with multiple vehicle types and time windows. Natural Science Council, 23(4), 526–536.

    Google Scholar 

  • Machado, A., Ramalho, G., Zucker, J. D., & Drogoul, A. (2002). Multi-agent patrolling: An empirical analysis of alternative architectures. In Proceedings of the 3rd international workshop on multi-agent-based simulation II, MABS 2002 (pp. 155–170). Berlin: Springer.

  • Martin, O., Otto, S., & Felten, E. (1991). Large-step markov chains for the traveling salesman problem. Complex Systems, 5(3), 299–326.

    MATH  MathSciNet  Google Scholar 

  • Martin, O., Otto, S. W., & Felten, E. W. (1992). Large-step markov chains for the tsp incorporating local search heuristics. Operations Research Letters, 11, 219–224.

    Article  MATH  MathSciNet  Google Scholar 

  • Mataric, M. J., & Sukhatme, G. S. (2001). Task-allocation and coordination of multiple robots for planetary exploration. In Proceedings of the 10th international conference on advanced robotics, ICAR 2001 (pp. 61–70).

  • Nilsson, B. J. (1995). Guarding art galleries—methods for mobile guards. PhD Thesis, Lund University.

  • Okabe, A., Boots, B., Sugihara, K., & Chiu, S. N. (2000). Spatial tessellations: Concepts and applications of voronoi diagrams. Series in probability and statistics (2nd edn.). New York: John Wiley.

  • O’Rourke, J. (1987). Art gallery theorems and algorithms. New York: Oxford University Press.

    MATH  Google Scholar 

  • Packer, E. (2008). Computing multiple watchman routes. In C. C. McGeoch (Ed.), 7th International workshop on experimental algorithms, WEA 2008. Lecture notes in computer science (Vol. 5038, pp. 114–128). New York: Springer.

  • Packer, E. (2008). Robust geometric computing and optimal visibility coverage. Ph.D. thesis, Stony Brook, NY, USA (2008).

  • Rekleitis, I., New, A. P., Rankin, E. S., & Choset, H. (2008). Efficient boustrophedon multi-robot coverage: An algorithmic approach. Annals of Mathematics and Artificial Intelligence, 52(2–4), 109–142.

    Article  MATH  MathSciNet  Google Scholar 

  • Sak, T., Wainer, J., & Goldenstein, S. K. (2008). Probabilistic multiagent patrolling. In Proceedings of the 19th Brazilian symposium on artificial intelligence: Advances in artificial intelligence, SBIA 2008 (pp. 124–133). Berlin: Springer (2008).

  • Santana, H., Ramalho, G., Corruble, V., & Ratitch, B. (2004). Multi-agent patrolling with reinforcement learning. International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS, 2004, 1122–1129.

    Google Scholar 

  • Simmons, R., Apfelbaum, D., Burgard, W., Fox, D. Moors, M., Thrun, S., et al. (2000). Coordination for multi-robot exploration and mapping. In Proceedings of the national conference on artificial intelligence, AAAI 2000, Austin, TX (pp. 852–858).

  • Skiena, S. S. (1998). The algorithm design manual. New York: Springer.

    Google Scholar 

  • Tan, X. (2001). Fast computation of shortest watchman routes in simple polygons. Information Processing Letter, 77(1), 27–33.

    Article  MATH  Google Scholar 

  • Tomás, A., & Bajuelos, A. (2004). Quadratic-time linear-space algorithms for generating orthogonal polygons with a given number of vertices (pp. 117–126). New York: Springer.

  • Toth, P., & Vigo, D. (2002a). Models, relaxations and exact approaches for the capacitated vehicle routing problem. Discrete Applied Mathematics, 123(1–3), 487–512.

    Article  MATH  MathSciNet  Google Scholar 

  • Toth, P., & Vigo, D. (2002b). The vehicle routing problem. Philadelphia, PA: Society for Industrial Mathematics.

    Book  MATH  Google Scholar 

  • Urrutia, J. (2000). Art gallery and illumination problems. In Handbook of computational geometry (pp. 973–1027). Amsterdam: North-Holland (2000).

  • Vidal, R., Shakernia, O., Kim, H., Shim, D., & Sastry, S. (2002). Probabilistic pursuit-evasion games: Theory, implementation, and experimental evaluation. IEEE Transactions on Robotics and Automation, 18(5), 662–669.

    Article  Google Scholar 

  • Williams, K., & Burdick, J. (2006). Multi-robot boundary coverage with plan revision. In Proceedings of the IEEE international conference on robotics and automation, ICRA 2006 (pp. 1716–1723).

  • Yamauchi, B. (1998). Frontier-based exploration using multiple robots. In Proceedings of the second international conference on autonomous agents, AGENTS 1998 (pp. 47–53).

  • Zalik, B., & Clapworthy, G. J. (1999). A universal trapezoidation algorithm for planar polygons. Computers & Graphics, 23(3), 353–363.

    Article  Google Scholar 

  • Zheng, X., Jain, S., Koenig, S., & Kempe, D. (2005). Multi-robot forest coverage. In Proceedings of the IEEE/RSJ international conference on intelligent robots and systems, IROS 2005 (pp. 3852–3857).

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Acknowledgments

We are grateful to Dr. Will Evans and Dr. David Kirkpatrick of the Department of Computer Science, University of British Columbia for useful discussions on the work reported here. This work was supported by grants from the Natural Sciences and Engineering Research Council of Canada.

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  1. Department of Computer Science, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada

    Pooyan Fazli, Alireza Davoodi & Alan K. Mackworth

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  1. Pooyan Fazli
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Fazli, P., Davoodi, A. & Mackworth, A.K. Multi-robot repeated area coverage. Auton Robot 34, 251–276 (2013). https://doi.org/10.1007/s10514-012-9319-7

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