skip to main content
research-article

Tight Analysis of a Collisionless Robot Gathering Algorithm

Published:06 April 2017Publication History
Skip Abstract Section

Abstract

We consider the fundamental problem of gathering a set of n robots in the Euclidean plane that have a physical extent and hence cannot share their positions with other robots. The objective is to determine a minimum time schedule to gather the robots as close together as possible around a predefined gathering point avoiding collisions. This problem with minimum time objective has applications in many real-world scenarios including fast autonomous coverage formation. Cord-Landwehr et al. (in Proceedings of the International Conference on Current Trends in Theory and Practice of Computer Science, 2011) gave a local greedy algorithm in a fully synchronous setting and proved that, for the discrete version of the problem where robots’ movements are restricted to the positions on an integral grid, their algorithm solves this problem in O(nR) rounds, where R is the distance from the farthest initial robot position to the gathering point. In this article, we improve significantly the round complexity of their algorithm to R + 2 · (n - 1) rounds. This round complexity is obtained in the following modified model: (1) the viewing range of the robots is increased to three hops and (2) robots can additionally move to the diagonally opposite corner to a grid cell in one step—that is, they can traverse the two corresponding grid edges in one time step. We also prove that there are initial configurations of n robots in this problem where at least R+(n-1)/2 rounds are needed by any local greedy algorithm. Furthermore, we improve the lower bound to R + (n - 1) rounds for the algorithm of Cord-Landwehr et al. These results altogether provide a tight runtime analysis of their algorithm.

References

  1. Chrysovalandis Agathangelou, Chryssis Georgiou, and Marios Mavronicolas. 2013. A distributed algorithm for gathering many fat mobile robots in the plane. In PODC. ACM, New York, NY, 250--259. DOI:http://dx.doi.org/10.1145/2484239.2484266 Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Noa Agmon and David Peleg. 2004. Fault-tolerant gathering algorithms for autonomous mobile robots. In SODA. 1070--1078.Google ScholarGoogle Scholar
  3. H. Ando, Y. Oasa, I Suzuki, and M. Yamashita. 1999. Distributed memoryless point convergence algorithm for mobile robots with limited visibility. IEEE Trans. Robot. Automat. 15, 5 (1999), 818--828. DOI:http://dx.doi.org/10.1109/70.795787 Google ScholarGoogle ScholarCross RefCross Ref
  4. H. Ando, I Suzuki, and M. Yamashita. 1995. Formation and agreement problems for synchronous mobile robots with limited visibility. In ISIC. 453--460. DOI:http://dx.doi.org/10.1109/ISIC.1995.525098 Google ScholarGoogle ScholarCross RefCross Ref
  5. Ishai Ben-Aroya, Tamar Eilam, and Assaf Schuster. 1995. Greedy hot-potato routing on the two-dimensional mesh. Distrib. Comput. 9, 1 (1995), 3--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Laszlo Blazovics and Tams Lukovszki. 2014. Fast localized sensor self-deployment for focused coverage. In ALGOSENSORS, Paola Flocchini, Jie Gao, Evangelos Kranakis, and Friedhelm Meyer auf der Heide (Eds.). 83--94. DOI:http://dx.doi.org/10.1007/978-3-642-45346-5_7 Google ScholarGoogle ScholarCross RefCross Ref
  7. Kálmán Bolla, Tamás Kovacs, and Gábor Fazekas. 2012. Gathering of fat robots with limited visibility and without global navigation. In SIDE. Springer-Verlag, Berlin, 30--38. DOI:http://dx.doi.org/10.1007/978-3-642-29353-5_4 Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Philipp Brandes, Bastian Degener, Barbara Kempkes, and Friedhelm Meyer auf der Heide. 2013. Energy-efficient strategies for building short chains of mobile robots locally. Theor. Comput. Sci. 509 (2013), 97--112. DOI:http://dx.doi.org/10.1016/j.tcs.2012.10.056 Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Sruti Gan Chaudhuri and Krishnendu Mukhopadhyaya. 2010. Gathering asynchronous transparent fat robots. In ICDCIT. 170--175. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. R. Cohen and D. Peleg. 2004. Robot convergence via center-of-gravity algorithms. In SIROCCO. 79--88. Google ScholarGoogle ScholarCross RefCross Ref
  11. Reuven Cohen and David Peleg. 2005. Convergence properties of the gravitational algorithm in asynchronous robot systems. SIAM J. Comput. 34, 6 (2005), 1516--1528. DOI:http://dx.doi.org/10.1137/S0097539704446475 Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Andreas Cord-Landwehr, Bastian Degener, Matthias Fischer, Martina Hüllmann, Barbara Kempkes, Alexander Klaas, Peter Kling, Sven Kurras, Marcus Märtens, Friedhelm Meyer auf der Heide, Christoph Raupach, Kamil Swierkot, Daniel Warner, Christoph Weddemann, and Daniel Wonisch. 2011. Collisionless gathering of robots with an extent. In SOFSEM. 178--189. Google ScholarGoogle ScholarCross RefCross Ref
  13. Andreas Cord-Landwehr, Bastian Degener, Matthias Fischer, Martina Hüllmann, Barbara Kempkes, Alexander Klaas, Peter Kling, Sven Kurras, Marcus Märtens, Friedhelm Meyer auf der Heide, Christoph Raupach, Kamil Swierkot, Daniel Warner, Christoph Weddemann, and Daniel Wonisch. 2011. A new approach for analyzing convergence algorithms for mobile robots. In ICALP. 650--661. DOI:http://dx.doi.org/10.1007/978-3-642-22012-8_52 Google ScholarGoogle ScholarCross RefCross Ref
  14. Jurek Czyzowicz, Leszek Gasieniec, and Andrzej Pelc. 2009. Gathering few fat mobile robots in the plane. Theor. Comput. Sci. 410, 6--7 (2009), 481--499. DOI:http://dx.doi.org/10.1016/j.tcs.2008.10.005 Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Bastian Degener, Barbara Kempkes, Peter Kling, and Friedhelm Meyer auf der Heide. 2010b. A continuous, local strategy for constructing a short chain of mobile robots. In SIROCCO. 168--182. DOI:http://dx.doi.org/10.1007/978-3-642-13284-1_14 Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Bastian Degener, Barbara Kempkes, Tobias Langner, Friedhelm Meyer auf der Heide, Peter Pietrzyk, and Roger Wattenhofer. 2011. A tight runtime bound for synchronous gathering of autonomous robots with limited visibility. In SPAA. 139--148. DOI:http://dx.doi.org/10.1145/1989493.1989515 Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Bastian Degener, Barbara Kempkes, and Friedhelm Meyer auf der Heide. 2010a. A local O(n2) gathering algorithm. In SPAA. 217--223. DOI:http://dx.doi.org/10.1145/1810479.1810523 Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Ayan Dutta, Sruti Gan Chaudhuri, Suparno Datta, and Krishnendu Mukhopadhyaya. 2012. Circle formation by asynchronous fat robots with limited visibility. In ICDCIT. 83--93. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Taisuke Izumi, Tomoko Izumi, Sayaka Kamei, and Fukuhito Ooshita. 2009. Randomized gathering of mobile robots with local-multiplicity detection. In SSS. Springer-Verlag, Berlin, 384--398. DOI:http://dx.doi.org/10.1007/978-3-642-05118-0_27 Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Taisuke Izumi, Yoshiaki Katayama, Nobuhiro Inuzuka, and Koichi Wada. 2007. Gathering autonomous mobile robots with dynamic compasses: An optimal result. In DISC. Springer-Verlag, Berlin, 298--312. Google ScholarGoogle ScholarCross RefCross Ref
  21. Taisuke Izumi, Maria Gradinariu Potop-Butucaru, and Sébastien Tixeuil. 2010. Connectivity-preserving scattering of mobile robots with limited visibility. In SSS. Springer-Verlag, Berlin, 319--331. http://dl.acm.org/citation.cfm?id=1926829.1926858 Google ScholarGoogle ScholarCross RefCross Ref
  22. Barbara Kempkes, Peter Kling, and Friedhelm Meyer auf der Heide. 2012. Optimal and competitive runtime bounds for continuous, local gathering of mobile robots. In SPAA. 18--26. DOI:http://dx.doi.org/10.1145/2312005.2312009 Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. M. U. Khan, S. Li, Q. Wang, and Z. Shao. 2016a. Distributed multi-robot formation and tracking control in cluttered environment. TAAS 11, 2 (2016), 12:1--12:22.Google ScholarGoogle Scholar
  24. Muhammad Umer Khan, Shuai Li, Qixin Wang, and Zili Shao. 2016b. Formation control and tracking for co-operative robots with non-holonomic constraints - categories (2), (3). J. Intell. Robotic Syst. 82, 1 (2016), 163--174. DOI:http://dx.doi.org/10.1007/s10846-015-0287-y Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Ralf Klasing, Euripides Markou, and Andrzej Pelc. 2008. Gathering asynchronous oblivious mobile robots in a ring. Theor. Comput. Sci. 390, 1 (2008), 27--39. DOI:http://dx.doi.org/10.1016/j.tcs.2007.09.032 Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Peter Kling and Friedhelm Meyer auf der Heide. 2011. Convergence of local communication chain strategies via linear transformations: or how to trade locality for speed. In SPAA. 159--166. DOI:http://dx.doi.org/10.1145/1989493.1989517 Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Jarosaw Kutyowski and Friedhelm Meyer Auf Der Heide. 2009. Optimal strategies for maintaining a chain of relays between an explorer and a base camp. Theor. Comput. Sci. 410, 36 (2009), 3391--3405. DOI:http://dx.doi.org/10.1016/j.tcs.2008.04.010 Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Xu Li, Hannes Frey, Nicola Santoro, and Ivan Stojmenovic. 2009a. Focused-coverage by mobile sensor networks. In MASS. 466--475. Google ScholarGoogle ScholarCross RefCross Ref
  29. Xu Li, Hannes Frey, Nicola Santoro, and Ivan Stojmenovic. 2009b. Localized sensor self-deployment for guaranteed coverage radius maximization. In ICC. 1--5. Google ScholarGoogle ScholarCross RefCross Ref
  30. Xu Li, Hannes Frey, Nicola Santoro, and Ivan Stojmenovic. 2011. Strictly localized sensor self-deployment for optimal focused coverage. IEEE Trans. Mobile Comput. 10, 11 (2011), 1520--1533. DOI:http://dx.doi.org/10.1109/TMC.2010.261 Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Tamás Lukovszki and Friedhelm Meyer auf der Heide. 2014. Fast collisionless pattern formation by anonymous, position-aware robots. In OPODIS. 248--262. DOI:http://dx.doi.org/10.1007/978-3-319-14472-6_17 Google ScholarGoogle ScholarCross RefCross Ref
  32. Linda Pagli, Giuseppe Prencipe, and Giovanni Viglietta. 2012. Getting close without touching. In SIROCCO. 315--326. DOI:http://dx.doi.org/10.1007/978-3-642-31104-8_27 Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Giuseppe Prencipe. 2007. Impossibility of gathering by a set of autonomous mobile robots. Theor. Comput. Sci. 384, 2--3 (2007), 222--231. DOI:http://dx.doi.org/10.1016/j.tcs.2007.04.023 Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. G. Sharma, C. Busch, S. Mukhopadhyay, and C. Malveaux. 2015. Tight analysis of a collisionless robot gathering algorithm. In IROS 5189--5194. Google ScholarGoogle ScholarCross RefCross Ref
  35. Samia Souissi, Xavier Défago, and Masafumi Yamashita. 2006. Gathering asynchronous mobile robots with inaccurate compasses. In OPODIS. Springer-Verlag, Berlin, 333--349. DOI:http://dx.doi.org/10.1007/11945529_24 Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Tight Analysis of a Collisionless Robot Gathering Algorithm

            Recommendations

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in

            Full Access

            • Published in

              cover image ACM Transactions on Autonomous and Adaptive Systems
              ACM Transactions on Autonomous and Adaptive Systems  Volume 12, Issue 1
              March 2017
              113 pages
              ISSN:1556-4665
              EISSN:1556-4703
              DOI:10.1145/3071074
              Issue’s Table of Contents

              Copyright © 2017 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 6 April 2017
              • Accepted: 1 November 2016
              • Revised: 1 September 2016
              • Received: 1 January 2016
              Published in taas Volume 12, Issue 1

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • research-article
              • Research
              • Refereed

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader