Abstract
How can a mobile robot measure the area of a closed region that is beyond its immediate sensing range? This problem, which we name as blind area measurement, is inspired from scout worker ants who assess potential nest cavities. We first review the insect studies that have shown that these scouts, who work in dark, seem to assess arbitrary closed spaces and reliably reject nest sites that are small for the colony. We briefly describe the hypothesis that these scouts use “Buffon’s needle method” to measure the area of the nest. Then we evaluate and analyze this method for mobile robots to measure large closed regions. We use a simulated mobile robot system to evaluate the performance of the method through systematic experiments. The results showed that the method can reliably measure the area of large and rather open, closed regions regardless of their shape and compactness. Moreover, the method’s performance seems to be undisturbed by the existence of objects and by partial barriers placed inside these regions. Finally, at a smaller scale, we partially verified some of these results on a real mobile robot platform.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Braitenberg, V. 1984. Vehicles. MIT Press, Cambridge, MA, USA.
Camazine, S., Franks, N.R., Sneyd, J., Bonabeau, E., Deneubourg, J.-L., and Theraulaz, G. 2001. Self-Organization in Biological Systems. Princeton University Press, Princeton, NJ, USA. ISBN: 0691012113.
Choset, H. 2001. Coverage for robotics—A survey of recent results. Annals of Mathematics and Artificial Intelligence, 31(1–4):113–126.
Dissanayake, G., Durrant-Whyte, H., and Bailey, T. 2000. A computationally efficient solution to the simultaneous localisation and map building (SLAM) problem. Working notes of ICRA'2000 Workshop W4: Mobile Robot Navigation and Mapping.
Elfes, A. 1989. Occupancy grids: A probabilistic framework for robot perception and navigation. PhD thesis, Department of Electrical and Computer Engineering, Carnegie Mellon University.
Girgin, S. and Şahin, E. 2004. Blind area measurement with mobile robots. In Proceedings the 8th Conference on Intelligent Autonomous Systems (IAS 8). IOS Press, pp. 37–44.
Grasse, P. 1959. La reconstruction du nid et les coordinations inter-individuelles chez bellicositermes natalensis et cubitermes sp. la theorie de la stigmergie: Essai dínterpretation du comportement des termites constructeurs. Insectes Sociaux, 6:41–83.
Koenig, S., Szymanski, B., and Liu, Y. 2001. Efficient and inefficient ant coverage methods. Annals of Mathematics and Artificial Intelligence, 31(1–4):41–76.
Mallon, E.B. and Franks, N.R. 2000. Ants estimate area using Buffon's needle. In Proc. Royal Society London B, pp. 267:765–770.
Marshall, J.A.R., Kovacs, T., Dornhaus, A.R., and Franks, N.R. 2003. Simulating the evolution of ant behaviour in evaluating nest sites. In Advances in Artificial Life—Proceedings of the 7th European Conference on Artifical Life (ECAL). Number 2801. in: Lecture Notes in Artificial Intelligence, Springer Verlag, pp. 643–650.
Miglino, O., Lund, H.H., and Nolfi, S. 1995. Evolving mobile robots in simulated and real environments. Artificial Life, 2(4):417–434.
Mondada, F., Franzi, E., and Ienne, P. 1993. Miniaturisation: A tool for investigation in control algorithms. In Proceedings of the Third International Symposium on Experimental Robotics, Berlin, Springer-Verlag, pp. 501–513.
Mugford, S.T., Mallon, E.B., and Franks, N.R. 2001. The accuracy of Buffon’s needle: A rule of thumb used by ants to estimate area. Behavioral Ecology, 12:655–658.
Şahin, E. and Franks, N.R. 2002a. Measurement of space: From ants to robots. In Proceedings of WGW 2002a: EPSRC'BBSRC International Workshop Biologically-Inspired Robotics: The Legacy of W. Grey Walter, Bristol, UK, pp. 241–247.
Şahin, E. and Franks, N.R. 2002b. Simulation of nest assessment behavior by ant scouts. In Proceedings of ANTS 2002: From Ants Colonies to Artificial Ants, 3rd International Workshop on Ants Algorithm, Lecture Notes in Computer Science 2463: Ant Algorithms, Brussels, Belgium, Springer-Verlag, pp. 274–282.
Santalo, L.A. 1976. Integral Geometry and Geometric Probability. Vol. I of Encyclopedia of Mathematics and its Applications. Addison-Wesley, Reading, MA.
Svennebring, J. and Koenig S. 2003. Trail-laying robots for robust terrain coverage. In Proceedings. ICRA'03. IEEE International Conference on Robotics and Automation, pp. 75–82.
Thrun, S. 2003. Robotic mapping: A survey. In G. Lakemeyer and B. Nebel (eds.), Exploring Artificial Intelligence in the New Millenium. Morgan Kaufmann, pp. 1–35.
Wagner, I.A. and Bruckstein, A.M. 2001. From ants to a(ge)nts: A special issue on ant-robotics. Annals of Mathematics and Artificial Intelligence, 31(1–4):1–5.
Wagner, I.A., Lindenbaum, M., and Bruckstein, A.M. 2000. MAC Versus PC: Determinism and randomness as complementary approaches to robotic exploration of continuous unknown domains. The International Journal of Robotics Research, 19(1):12–31.
Author information
Authors and Affiliations
Additional information
Erol Şahin is an Assistant Professor at the Computer Engineering Department of Middle East Technical University (METU), Turkey. He has a B.Sc. in Electrical and Electronics Engineering from Bilkent University in 1991, Turkey, a M.Sc. in Computer Engineering from METU in 1995, and a Ph.D. in Cognitive and Neural Systems from Boston University, USA, 2000. He worked as a post-doctoral fellow at IRIDIA, Universitè Libre de Bruxelles, Belgium, for the Swarm-bots project (http://swarm-bots.org) prior to assuming his current position at METU in 2002. Dr. Şahin co-edited a special issue of Autonomous Robots on Swarm Robotics (2004), and a State-of-the-art survey book on Swarm Robotics (2005), the first book devoted to the topic. He has also been the co-organizer of two Swarm Robotics Workshops in 2004 and 2006. He was awarded a Career Project Award by the Turkish Scientific and Technical Council to develop controllable robotic swarms. He has also been working on the MACS project (http://macs-eu.org) as a partner, a cognitive robotics project funded under the Cognitive Systems strategic objective of FP6, to develop an affordance-based robot control architecture. Dr. Şahin is the head of the KOVAN Research Laboratory, at the Computer Engineering Department of METU.
Sertan Girgin is a graduate student at the Computer Engineering Department of Middle East Technical University (METU), Turkey. He holds two B.Sc. degrees, one in Computer Engineering and the other in Mathematics, and an M.Sc. in Computer Engineering from METU, 2003. He is currently visiting researcher at the Department of Computer Science, University of Calgary. His research interests include distributed AI, multi-agent systems and reinforcement learning.
Emre Uğur is a graduate student at the Computer Engineering Department of Middle East Technical University (METU), Turkey. He has a B.Sc. degree in Computer Engineering from METU, 2003. He has worked for the Swarm-bots project (http://swarm-bots.org), both as an intern at IRIDIA, Universitè Libre de Bruxelles, Belgium, in 2001, and later as a graduate student at METU, Turkey. Since 2004, he has been working as a researcher for the MACS project (http://macs-eu.org), a cognitive robotics project funded under the Cognitive Systems strategic objective of FP6, and is close to finishing his M.Sc. thesis on “affordance-based learning of traversibility on a mobile robot”. His research interests include swarm and cognitive robotic systems.
Rights and permissions
About this article
Cite this article
Şahin, E., Girgin, S. & Uğur, E. Area measurement of large closed regions with a mobile robot. Auton Robot 21, 255–266 (2006). https://doi.org/10.1007/s10514-006-9719-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10514-006-9719-7