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Basic Visual and Motor Agents for Increasingly Complex Behavior Generation on a Mobile Robot

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Abstract

Present work addresses the guidelines that have been followed to construct basic behavioral agents for visually guided navigation within the framework of a hierarchical architecture. Visual and motor interactions are described within this generic framework that allows for an incremental development of behavior from an initial basis set. Basic locomotion agents as, Stop&Backward, Avoid, and Forward are implemented by means of fuzzy knowledge bases to deal with the uncertainty and imprecision inherent to real systems and environments. Basic visual agents as, Saccadic, Find_Contour, and Center are raised under a space-variant representation pursuing an anthropomorphic approach. We illustrate how a complex behavior results from the combination of lower level agents always connected to the basic motor agents. The proposed methodology is validated on a caterpillar mobile robot in navigation tasks directed by an object description.

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References

  • Albus, J.S. 1992. RSC:Areference model architecture for intelligent control. IEEE Computer, Special Issue on Computer Architectures for Intelligent Machines.

  • Arbib, M.A. 1981. Perceptual structures and distributed motor control. Handbook of Physiology-The Nervous System II. Motor Control, Amer Physiol. Soc.

  • Arbib, M.A. and Cobas, A. 1991. Schemas for prey-catching in frog and toad. From Animals to Animats: Proc. of the First Int. Conf. on Simulation of Adaptive Behavior, pp. 142-151.

  • Arkin, R.C. 1989. Motor schema-based mobile robot navigation. Int. J. Robotics Res., 8(4):92-112.

    Google Scholar 

  • Arkin, R.C. 1990. Integrating behavioral, perceptual, and world knowledge in reactive navigation. Robotics and Autonomous Systems, 6:105-122.

    Google Scholar 

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

    Google Scholar 

  • Brooks, R.A. 1991. Intelligence without representation. Artificial Intelligence, 47:139-160.

    Article  Google Scholar 

  • Bustos, P., Recio, F., Guinea, D., and Garcia-Alegre, M.C. 1995. Cortical representations in active vision on a network of transputers. In Proc. of First ECPD Int. Conf. on Advanced Robotics and Intelligent Automation, Athens, pp. 259-264.

  • Connell, J.H. 1991. SSS: A hybrid architecture applied to robot navigation. In IEEE Int. Conf. on Robotics and Automation, Nice, pp. 2719-2724.

  • Corbacho, F. and Arbib, M.A. 1995. Learning to detour. Adaptive Behavior, 3(4):419-468.

    Google Scholar 

  • Garcia-Alegre, M.C., Ribeiro, A., Gasós, J., and Salido, J. 1993. Optimization of fuzzy behavior-based robot navigation in partially known industrial environments. In The Third Int. Conf. on Industrial Fuzzy Control and Intelligent Systems, Houston, TX, pp. 50-54.

  • Garcia-Alegre, M.C., Bustos, P., and Guinea, D. 1995. Complex behavior generation on autonomous robots: A case study. In Proc. of IEEE on System, Man, and Cybernetics, Vancouver, B.C., pp. 1729-1734.

  • Gasós, J., Garcia-Alegre, M.C., and Garcia, R. 1992. Fuzzy strategies for the navigation of autonomous mobile robots. Fuzzy Engineering towards Human Friendly Systems, IOS Press: Amsterdam, Holland.

    Google Scholar 

  • Guinea, D., García-Alegre, M.C., Kalata, P., Lacaza, A., and Meystel, A. 1993. Robot learning to walk: An architectural problem for intelligent controllers. Eighth IEEE Int. Symp. on Intelligent Control, Chicago, IL, pp. 493-498.

  • Guinea, D., Sánchez, G., Bustos, P., and García-Alegre, M.C. 1995. A distributed architecture for active perception in autonomous robots. IEEE Int. Conf. Syst. Man and Cyber., Vancouver, Canada, pp. 1740-1745.

  • Hayes-Roth, B. 1995. An architecture for adaptive intelligent systems. Artificial Intelligence, Special Issue on Agents and Interactivity, 72(1-2):329-365.

    Google Scholar 

  • Luck, M. and d'Inverno, M. 1995. A formal framework for agency and autonomy. In Proc. First Int. Conf. on Multi-Agent Systems, San Francisco, CA, pp. 254-260.

  • Maes, P. 1990. Situated agents can have goals. Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back, MIT Press/Bradford Books: Cambridge, CA.

    Google Scholar 

  • Maes, P. 1991. A bottom-up mechanism for behavior-selection in an artificial creature. In From Animals to Animats, Proc. of the First Int. Conf. on the Simulation of Adaptive Behavior, MIT Press/Bradford Books: Cambridge, MA.

    Google Scholar 

  • Mataric, M. 1994. Interaction and intelligent behavior. M.I.T. Artif. Intell. Lab., Massachusetts Inst. Technol., Cambridge, MA, A.I. Memo. 1495.

    Google Scholar 

  • Mataric, M. 1995. Issues and approaches in the design of collective autonomous agents. Robotics and Autonomous Systems, 16(2-4): 321-331.

    Article  Google Scholar 

  • Mataric, M. 1996. Learning in multi-robot systems. Lectures Notes in Artificial Intelligence (LNAI), 1042:152-163.

    Google Scholar 

  • Mataric, M. 1997. Studying the role of embodiment in cognition. Cyber. & Systems, 28(6):457-570.

    Google Scholar 

  • McFarland and Bösser, T. 1993. Intelligent Behavior in Animal and Robots, MIT Press: Cambridge, MA.

    Google Scholar 

  • Minsky, M.L. 1986. The Society of Mind, Simon & Schuster Ed.: New York.

  • Minsky, M.L. 1994. A conversation about agents. Communication of the ACM, 22-29.

  • Newell, A. 1990. Unified Theories of Cognition, Harvard University Press: Cambridge, MA.

    Google Scholar 

  • Nillson, N.J. 1971. Problem Solving Methods in Artificial Intelligence, McGraw Hill.

  • Noton, D. and Stark, L. 1971. Eye movements and visual perception. Scientific American, 224(6):34-43.

    Google Scholar 

  • Panerai, F., Capurro, C., and Sandini, G. 1995. Space variant vision for an active camera mount. LIRA-TR 1/95. LIRA-DIST, University of Genoa.

  • Recio, F. 1995. Tracking monocular. Informe Técnico. 09/95, Dept. of Systems, IAI/Consejo Superior de Investigaciones Científicas.

  • Simon, H. 1969. The Sciences of the Artificial, MIT Press: Cambridge, MA.

    Google Scholar 

  • Steels, L. 1994. Building agents with autonomous behavior systems. In The Artificial life route to Artificial Intelligence: Building Situated Embodied Agents, Lawrence Erlbaum Assoc.: New Haven, MA.

    Google Scholar 

  • Tinbergen, N. 1951. The Study of Instinct, Oxford University Press.

  • Tistarelli, M. and Sandini, G. 1992. Dynamic aspects in active vision. CVGPI: Image understanding, 1(56):108-129.

    Google Scholar 

  • Van den Velde, W. 1995. Cognitive architectures-from knowledge level to structural coupling. In The Biology and Technology of Intelligent Autonomous Agents, Springer Verlag.

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Authors and Affiliations

  1. Consejo Superior de Investigaciones Cientificas (CSIC), Instituto de Automática Industrial (IAI), 28500 Arganda del Rey, Madrid, Spain

    Maria C. Garcia-Alegre & Felicidad Recio

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  1. Maria C. Garcia-Alegre
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  2. Felicidad Recio
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Garcia-Alegre, M.C., Recio, F. Basic Visual and Motor Agents for Increasingly Complex Behavior Generation on a Mobile Robot. Autonomous Robots 5, 19–28 (1998). https://doi.org/10.1023/A:1008808908196

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  • DOI: https://doi.org/10.1023/A:1008808908196