Skip to main content
SpringerLink
Log in

Task Modelling in Collective Robotics

  • Chapter
Robot Colonies

Abstract

Does coherent collective behaviour require an explicit mechanism of cooperation? In this paper, we demonstrate that a certain class of cooperative tasks, namely coordinated box manipulation, are possible without explicit communication or cooperation mechanisms. The approach relies on subtask decomposition and sensor preprocessing. A framework is proposed for modelling multi-robot tasks which are described as a series of steps with each step possibly consisting of substeps. Finite state automata theory is used to model steps with state transitions specified as binary sensing predicates called perceptual cues. A perceptual cue (Q), whose computation is disjoint from the operation of the automata, is processed by a 3-level finite state machine called a Q-machine. The model is based on entomological evidence that suggests local stimulus cues are used to regulate a linear series of building acts in nest construction. The approach is designed for a redundant set of homogeneous mobile robots, and described is an extension of a previous system of 5 box-pushing robots to 11 identical transport robots. Results are presented for a system of physical robots capable of moving a heavy object collectively to an arbitrarily specified goal position. The contribution is a simple task-programming paradigm for mobile multi-robot systems. It is argued that Q-machines and their perceptual cues offer a new approach to environment-specific task modelling in collective robotics.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  • Agah, Arvin and Bekey, George 1995. Learning by trying in an autonomous multi-robot system. In submitted to I EEE/RSJ International Conference on Intelligent Robots and Systems.

    Google Scholar 

  • Altenburg, Karl 1994. Adaptive resource allocation for a multiple mobile robot system using communication. CSOR TR-9404, North Dakota State University.

    Google Scholar 

  • Altenburg, Karl and Pavivic, Mark 1993. Initial results of the use of inter-robot communication for a multiple, mobile robotic system. In Proceedings of the Dynamically Interacting Robots IJCAI-93 Workshop.

    Google Scholar 

  • Arkin, Ronald C. 1989. Motor schema based mobile robot navigation. International Journal of Robotics Research, 8 (4): 92–112.

    Article  Google Scholar 

  • Arkin, Ronald C. 1992. Cooperation without communication: Multiagent schema-based robot navigation. Journal of Robotic Systems, 9 (3): 351–364.

    Article  Google Scholar 

  • Arkin, Ronald C. 1993. Survivable robotic systems: Reactive and homeostatic control. In Robotics and Remote Systems for Hazardous Environments, M. Jamshida and P. Eicker (Eds.), Prentice Hall: Englewood Cliffs, New Jersey, vol. I, no. 7, pp. 135–154.

    Google Scholar 

  • Arkin, Ronald C. and Hobbs, J. David 1992. Dimensions of communication and social organization in multi-agent robotic systems. In Second International Conference on Simulation of Adaptive Behavior, J.A. Meyer, H. Roitblat, and S. Wilson ( Eds. ), MIT Press, pp. 486–493.

    Google Scholar 

  • Arkin, Ronald C., Balch, Tucker, and Nitz, Elizabeth 1993. Communication of behavioral state in multi-agent retrieval tasks. In 1993 IEEE International Conference on Robotics and Automation, vol. 3, pp. 588–594.

    Google Scholar 

  • Arkin, Ronald C., and McKenzie, Douglas 1994. Temporal coordination of perceptual algorithms for a mobile robot navigation. IEEE Transactions on Robotics and Automation, 10 (3): 276–286.

    Article  Google Scholar 

  • Asama, Hajime, Habib, Maki K., Endo, Isao, Ozaki, Koichi, Matsumoto, Akihiro, and Ishida, Yoshiki 1991. Functional distribution among multiple mobile robots in an autonomous and decentralized robot system. In 1991 IEEE International Conference on Robotics and Automation, pp. 1921–1926.

    Google Scholar 

  • Asami, Shuji 1994. Robots in Japan: Present and future. IEEE Robotics and Automation Magazine, pp. 22–26.

    Google Scholar 

  • Baerends, G.P. and Kruijt, J.P. 1973. Stimulus selection. In Constraints on Learning: Limitations and Predispositions, R.A. Hinde and J. Stevenson-Hinde ( Eds. ), Academic Press.

    Google Scholar 

  • Balch, Tucker and Arkin, Ronald C. 1994. Communication in reactive multiagent robotic systems. Autonomous Robots, 1: 125.

    Article  Google Scholar 

  • Bay, John S. 1995. Design of the army-ant cooperative lifting robot. IEEE Robotics and Automation Magazine, pp. 36–43.

    Google Scholar 

  • Braitenberg, Valentino 1984. Vehicles: Experiments in Synthetic Psychology. MIT Press.

    Google Scholar 

  • Brooks, Rodney A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, RA-2(1): 14–23.

    Google Scholar 

  • Caloud, Philippe, Choi, Wonyun, Latombe, Jean-Claude, Pape, Claude Le, and Yim, Mark 1990. Indoor automation with many mobile robots. In 1990 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 67–72.

    Google Scholar 

  • Cao, Y. Uny, Fukunaga, Alex S., Kahng, Andrew B., and Meng, Frank 1995. Cooperative mobile robotics: Antecedents and directions. In 1995 IEEE International Conference on Intelligent Robots and Systems, 1: 226–234.

    Google Scholar 

  • Donald, Bruce, Jennings, James, and Rus, Daniela 1994. Analyzing teams of cooperating mobile robots. In 1994 IEEE International Conference on Robotics and Automation, pp. 1896–1903.

    Google Scholar 

  • Doty, Keith L. and Van Aken, Ronald, E. 1993. Swarm robot materials handling paradigm for a manufacturing workcell. In 1993 IEEE International Conference on Robotics and Automation, L77: 87–82.

    Google Scholar 

  • Downing, H.A. and Jeanne, R.L. 1988. Nest construction by the paper wasp, Polistes: A test of stigmergy theory. Animal Behaviour, 36: 1729–1739.

    Article  Google Scholar 

  • Downing, H.A. and Jeanne, R.L. 1990. The regulation of complex building behaviour in the paper wasp, polistes fuscatus (insecta, hymenoptera, vespidae). Animal Behaviour, 39: 105–124.

    Article  Google Scholar 

  • Drouin, M., Abou-Kandi, H., and Mariton, M. 1991. Control of Complex Systems: Methods and Technology,Plenum Press.

    Google Scholar 

  • Engelberger, Joseph F. 1989. Robotics in Service. Kogan Page Ltd.

    Google Scholar 

  • Franks, Nigel R. 1986. Teams in social insects: Group retrieval of prey by army ants. Behavioral Ecology and Sociobiology, 18: 425–429.

    Article  Google Scholar 

  • Grassé, P. 1959. La reconstruction du nid et les coordinations interindividuelles chez bellicositermes natalensi, s et cubitermes sp. la théorie de la stigmergie: essai d’interpré. Insectes Sociaux, 6: 41–81.

    Article  Google Scholar 

  • Kube, C. Ronald 1992. Collective robotic intelligence: A control theory for robot populations. Master’s thesis, University of Alberta.

    Google Scholar 

  • Kube, C. Ronald and Zhang, Hong 1992. Collective robotic intelli gence. In Second International Conference on Simulation ofAdaptive Behavior, pp. 460–468.

    Google Scholar 

  • Kube, C. Ronald and Zhang, Hong 1993. Collective robotics: From social insects to robots. Adaptive Behavior, 2 (2): 189–219.

    Article  Google Scholar 

  • Kube, C. Ronald and Zhang, Hong 1994. Stagnation recovery behaviours for collective robotics. In 1994 IEEE/RSJ/G1 International Conference on Intelligent Robots and Systems, vol. 3, pp. 1883–1890.

    Google Scholar 

  • Kube, C. Ronald and Zhang, Hong 1996. The use of perceptual cues in multi-robot box-pushing. Submitted to the Journal Robotica special issue on interacting robots.

    Google Scholar 

  • Luo, Ren C. and Kay, Michael G. 1989. Multisensor integration and fusion in intelligent systems. IEEE Transactions on Systems, Man, and Cybernetics, 19 (5): 901–931.

    Article  Google Scholar 

  • Mataric, Maja J. 1992. Minimizing complexity in controlling a mobile robot population. In 1992 IEEE International Conference on Robotics and Automation, pp. 830–835.

    Google Scholar 

  • Mataric, Maja J. 1994. Interaction and intelligent behavior. Ph.D. Thesis, Massachusetts Institute of Technology.

    Google Scholar 

  • Mataric, Maja J., Nilsson, Martin, and Kristian T. Simsarian 1995. Cooperative multi-robot box-pushing. In 1995 IEEE International Conference on Intelligent Robots and Systems,vol. 3, pp. 556–561. McFarland, David and Bosser, Thomas 1993. Intelligent Behavior in Animals and Robots,MIT Press.

    Google Scholar 

  • Metz, Hans A.J. 1977. State space models for animal behaviour. Annals of Systems Research, 6: 65–109.

    Article  Google Scholar 

  • Moffett, M.W. 1988. Cooperative food transport by an asiatic ant. National Geographic Research, 4 (3): 386–394.

    Google Scholar 

  • Moffett, M.W. 1992. Ant foraging. National Geographic Research Exploration, 8 (2): 220–231.

    Google Scholar 

  • Moser, J.C. 1970. Pheromones of social insects. In Control of Insect Behavior by Natural Products, D. Wood, R. Silverstein, and M. Nakajima (Eds.), Academic Press, pp. 161–178.

    Google Scholar 

  • Noreils, Fabrice R. 1992a. An architecture for cooperative and autonomous mobile robots. In 1992 IEEE International Conference on Robotics and Automation, pp. 2703–2710.

    Google Scholar 

  • Noreils, Fabrice R. 1992b. Coordinated protocols: An approach to formalize coordination between mobile robots. In 1992IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 717–724.

    Google Scholar 

  • Noreils, Fabrice R. 1992e. Multi-robot coordination for battlefield strategies. In 1992 IEEE/RSJlnternational Conference on Intelligent Robots and Systems, pp. 1777–1784.

    Google Scholar 

  • Ota, Jun and Arai, Tamio 1993. Motion planning of multiple mobile robots using dynamic groups. In 1993 IEEE International Conference on Robotics and Automation, vol. 2, pp. 28–33.

    Google Scholar 

  • Ozaki, Koichi, Asama, Hajime, Ishida, Yoshiki, Matsumoto, Akihiro, Yokota, Kazutaka, Kaetsu, Hayato, and Endo, lsao 1993. Synchronized motion by multiple mobile robots using communication. In Proceedings of the 1993 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1164–1169.

    Google Scholar 

  • Parker, Lynne E. 1993. Designing control laws for cooperative agent teams. In 1993 IEEE International Conference on Robotics and Automation, vol. 3, pp. 582–587.

    Google Scholar 

  • Parker, Lynne E. 1994. ALLIANCE: An architecture for fault tolerant, cooperative control of heterogeneous mobile robots. In 1994 IEEE/RSJ/GI International Conference on Intelligent Robots and Systems, pp. 776–783.

    Google Scholar 

  • Schricker, B. 1965. Die orientierung der honigbiene in der dammerung zugleich ein beitrag zur frage der ocellenfunktion bei bienen. Zeitschrift fur Vergleichende Physiologie, 49: 420–458.

    Article  Google Scholar 

  • Seitz, A. 1940. Die paarbildung bei einigen cichliden i. z. Tierpsychol, 4: 40–84.

    Google Scholar 

  • Shibata, Takanori and Fukuda, Toshio 1993. Coordinative behavior by genetic algorithm and fuzzy in evolutionary multi-agent system. In 1993 IEEE International Conference on Robotics and Automation, vol. 1, pp. 760–765.

    Google Scholar 

  • Silby, Richard and McFarland, David 1974. A state-space approach to motivation. In Motivational Control Systems Analysis, D.J. McFarland (Ed.), Academic Press, pp. 213–250.

    Google Scholar 

  • Stilwell, Daniel J. and Bay, John S. 1993. Toward the development of a material transport system using swarms of ant-like robots. In 1993 IEEE International Conference on Robotics and Automation, vol. 1, pp. 766–771.

    Google Scholar 

  • Sudd, J.H. 1960. The transport of prey by an ant, pheidole crassindoa. Behaviour, 16 (3–4): 295–308.

    Article  Google Scholar 

  • Sudd, J.H. 1965. The transport of prey by ants. Behaviour, 25 (3–4): 234–271.

    Article  Google Scholar 

  • Sudd, John 1963. How insects work in groups. Discovery, pp. 15–19.

    Google Scholar 

  • Tremblay, Marc R. and Cutkosky, Mark R. 1995. Using sensor fusion and contextual information to perform event detection during a phase-based manipulation task. In 1995 IEEE International Conference on Intelligent Robots and Systems, pp. 262–267.

    Google Scholar 

  • Wang, P.K.C. 1991. Navigation strategies for multiple autonomous mobile robots moving in formation. Journal of Robotic Systems, 8 (2): 177–195.

    Article  MATH  Google Scholar 

  • Wehner, Rudiger 1987. Matched filters-Neural models of the external world. Journal of Comparative Physiology A, 161: 511–531.

    Article  Google Scholar 

  • Wehner, R. and Srinivasan, M.V. 1984. The world as the insect secs it. In Insect Communications, T. Lewis (Ed.), Academic Press, pp. 29–47.

    Google Scholar 

  • Wilson, E.O. 1971. The Insect Societies. The Belkap Press of Harvard University Press.

    Google Scholar 

  • Wilson, Stewart W. 1990. The animal path to AI. In First International Conference on Simulation ofAdaptive Behavior, MIT Press, pp. 15–21.

    Google Scholar 

  • Wilson, E.O., Durlach, N.I., and Roth, L.M. 1958. Chemical releasers of necrophoric behavior in ants. Psyche, 65 (4): 108–114.

    Article  Google Scholar 

  • Zeil, J., Nalbach, G., and Nalbach, H.O. 1986. Eyes, eye stalks and the visual world of semi-terrestial crabs. Journal of Comparative Physiology A, 159: 801–811.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, T6G 2H1

    C. Ronald Kube & Hong Zhang

Authors
  1. C. Ronald Kube
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology, USA

    Ronald C. Arkin

  2. University of Southern California, USA

    George A. Bekey

Rights and permissions

Reprints and permissions

Copyright information

© 1997 Springer Science+Business Media New York

About this chapter

Cite this chapter

Kube, C.R., Zhang, H. (1997). Task Modelling in Collective Robotics. In: Arkin, R.C., Bekey, G.A. (eds) Robot Colonies. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-6451-2_3

Download citation

  • DOI: https://doi.org/10.1007/978-1-4757-6451-2_3

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5175-5

  • Online ISBN: 978-1-4757-6451-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation