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: A reference 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—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 Animais: 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.
Arkin, R.C. 1990. Integrating behavioral, perceptual, and world knowledge in reactive navigation. Robotics and Autonomous Systems, 6:105–122.
Brooks, R.A. 1986. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation, RA-2:14–23.
Brooks, R.A. 1991. Intelligence without representation. Artificial Intelligence, 47:139–160.
Bustos, P., Recio, F., Guinea, D., and Garcia-Alegre, M.C. 1995. Cortical representations in active vision on a network of transputers. In Prot: 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.
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.
Guinea, D., Garcia-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 Garíia-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.
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.
Maes, P. 1991. A bottom-up mechanism for behavior-selection in an artificial creature. In From Animals to Animais, Proc. of the First Int. Conf. on the Simulation of Adaptive Behavior, MIT Press/Bradford Books: Cambridge, MA.
Mataric, M. 1994. Interaction and intelligent behavior. M.I.T. Artif. Intell. Lab., Massachusetts Inst. Technol., Cambridge, MA, A.I. Memo. 1495.
Mataric, M. 1995. Issues and approaches in the design of collective autonomous agents. Robotics and Autonomous Systems, 16(2–4): 321–331.
Mataric, M. 1996. Learning in multi-robot systems. Lectures Notes in Artificial Intelligence (LNAI), 1042:152–163.
Mataric, M. 1997. Studying the role of embodiment in cognition. Cyber. & Systems, 28(6):457–570.
McFarland and Bösser, T. 1993. Intelligent Behavior in Animal and Robots, MIT Press: Cambridge, MA.
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.
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.
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.
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.
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.
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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Garcia-Alegre, M.C., Recio, F. (1998). Basic Visual and Motor Agents for Increasingly Complex Behavior Generation on a Mobile Robot. In: Bekey, G.A. (eds) Autonomous Agents. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5735-7_3
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DOI: https://doi.org/10.1007/978-1-4615-5735-7_3
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