Abstract
Advancing technologies have enabled simple mobile robots that collaborate to perform complex tasks. Understanding how to achieve such collaboration with simpler robots leverages these advances, potentially allowing more robots for a given cost and/or decreasing the cost of deploying a fixed number of robots. This paper is a step toward understanding the algorithmic strengths and weaknesses of robots that are identical mobile finite-state machines (FSMs)—FSMs being the avatar of “simple” digital computers. We study the ability of (teams of) FSMs to identify and search within varied-size quadrants of square \(n \times n\)) meshes of tiles—such meshes being the avatars of tesselated geographically constrained environments. Each team must accomplish its assigned tasks scalably—i.e., in arbitrarily large meshes (equivalently, for arbitrarily large values of \(n\)). Each subdivision of a mesh into quadrants is specified via a pair of fractions \(\langle \varphi , \psi \rangle \), where \(0 < \varphi , \psi < 1\), chosen from a fixed, finite repertoire of such pairs. The quadrants specified by the pair \(\langle \varphi , \psi \rangle \) are delimited by a horizontal line and a vertical line that cross at anchor mesh-tile \(v^{(\varphi , \psi )} = \langle \lfloor \varphi (n-1) \rfloor , \lfloor \psi (n-1) \rfloor \rangle \). The current results: \(\bullet \) A single FSM cannot identify tile \(v^{(\varphi , \psi )}\) in meshes of arbitrary sizes, even for a single pair \(\langle \varphi , \psi \rangle \)—except when \(v^{(\varphi , \psi )}\) resides on a mesh-edge. \(\bullet \) A pair of identical FSMs can identify tiles \(v^{(\varphi _i, \psi _i)}\) in meshes of arbitrary sizes, for arbitrary fixed finite sets of \(k\) pairs \(\{\langle \varphi _i, \psi _i \rangle \}_{i=1}^k\). The pair can sweep each of the resulting quadrants in turn. \(\bullet \) Single FSMs can always verify (for all pairs and meshes) that all of the tiles of each quadrant are labeled in a way that is unique to that quadrant. This process parallelizes linearly for teams of FSMs.
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References
Adler, F., Gordon, D.: Information collection and spread by networks of patrolling ants. Am. Nat. 140, 373–400 (1992)
Basu, P., Redi, J.: Movement control algorithms for realization of fault-tolerant ad hoc robot networks. IEEE Network 18(4), 36–44 (2004)
Bender, M., Slonim, D.: The power of team exploration: two robots can learn unlabeled directed graphs. In: Proceedings of the 35th IEEE Symposium on Foundations of Computer Science, pp. 75–85 (1994)
Blum, M., Sakoda, W.: On the capability of finite automata in 2 and 3 dimensional space. In: Proceedings of the 18th IEEE Symposium on Foundations of Computer Science, pp. 147–161 (1977)
Budach, L.: On the solution of the labyrinth problem for finite automata. Elektronische Informationsverarbeitung und Kybernetik (EIK) 11(10–12), 661–672 (1975)
Chen, L., Xu, X., Chen, Y., He, P.: A novel FSM clustering algorithm based on Cellular automata. IEEE/WIC/ACM International Conference on Intelligent Agent Technology (2004)
Cohen, R., Fraigniaud, P., Ilcinkas, D., Korman, A., Peleg, D.: Label-guided graph exploration by a finite automaton. ACM Trans. Algorithms 4(4), 1–18 (2008)
Geer, D.: Small robots team up to tackle large tasks. IEEE Distrib. Syst. Online 6(12), (2005)
Goles, E., Martinez, S. (eds.): Cellular Automata and Complex Systems. Kluwer, Amsterdam (1999)
Gruska, J., La Torre, S., Parente, M.: Optimal time and communication solutions of firing squad synchronization problems on square arrays, toruses and rings. In: Calude, C.S, Calude, E., Dinneen, M.J. (eds.) Developments in Language Theory. Lecture Notes in Computer Science, vol. 3340, pp. 200–211. Springer, Heidelberg (2004)
Marchese, F.: Cellular automata in robot path planning. In: Proceedings of the EUROBOT’96, pp. 116–125 (1996)
Müller, H.: Endliche automaten und labyrinthe. Elektronische Informationsverarbeitung und Kybernetik (EIK) 11(10–12), 661–672 (1975)
Rosenberg, A.L.: Cellular ANTomata: path planning and exploration in constrained geographical environments. Adv. Complex Syst. (2012) (to appear)
Rosenberg, A.L.: The Pillars of Computation Theory: State, Encoding, Nondeterminism. Universitext Series. Springer, Heidelberg (2009)
Rosenberg, A.L.: Ants in parking lots. In: Proceedigs of the 16th International Conference on Parallel Computing (EURO-PAR’10), Part II. Lecture Notes in Computer Science, vol. 6272, pp. 400–411. Springer, Heidelberg (2010)
Russell, R.: Heat trails as short-lived navigational markers for mobile robots. In: Proceedings of the International Conference on Robotics and Automation, pp. 3534–3539 (1997)
Spezzano, G., Talia, D.: The CARPET programming environment for solving scientific problems on parallel computers. Parallel Distrib. Comput. Pract. 1, 49–61 (1998)
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Rosenberg, A.L. (2013). Finite-State Robots in the Land of Rationalia. In: Gelenbe, E., Lent, R. (eds) Computer and Information Sciences III. Springer, London. https://doi.org/10.1007/978-1-4471-4594-3_1
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DOI: https://doi.org/10.1007/978-1-4471-4594-3_1
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