Optimal Torus Exploration by Oblivious Robots

  • Stéphane DevismesEmail author
  • Anissa Lamani
  • Franck Petit
  • Sébastien Tixeuil
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9466)


We consider autonomous robots that are endowed with motion actuators and visibility sensors. The robots we consider are weak, i.e., they are anonymous, uniform, unable to explicitly communicate, and oblivious (they do not remember any of their past actions). In this paper, we propose an optimal (w.r.t. the number of robots) solution for the terminating exploration of torus-shaped networks by a team of k such robots in the SSYNC model.

In more details, we first show that it is impossible to explore any simple torus of arbitrary size with (strictly) less than four robots, even if the algorithm is probabilistic. If the algorithm is required to be deterministic, four robots are also insufficient. This negative result implies that the only way to obtain an optimal algorithm (w.r.t. the number of robots participating to the algorithm) is to make use of probabilities.

Then, we propose a probabilistic algorithm that uses four robots to explore all simple tori of size \(\ell \times L\), where \(7 \le \ell \le L\). Hence, in such tori, four robots are necessary and sufficient to solve the (probabilistic) terminating exploration. As a torus can be seen as a 2-dimensional ring, our result shows, perhaps surprisingly, that increasing the number of possible symmetries in the network (due to increasing dimensions) does not necessarily come at an extra cost w.r.t. the number of robots that are necessary to solve the problem.



Authors are grateful to François Bonnet for valuable discussions and suggestions.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Stéphane Devismes
    • 1
    Email author
  • Anissa Lamani
    • 2
  • Franck Petit
    • 3
    • 4
  • Sébastien Tixeuil
    • 3
    • 5
  1. 1.VERIMAG, Université Joseph FourierSaint-martin-d’hèresFrance
  2. 2.Kyushu UniversityFukuokaJapan
  3. 3.LIP6, UPMC Sorbonne UniversitésParisFrance
  4. 4.INRIA, Projet-Team REGALParisFrance
  5. 5.Institut Universitaire de FranceParisFrance

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