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Betreff: Sensor Fusion and Planning with Perception–Action Network
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Kluwer Homepage Customer Service Webmaster Journal Homepage Subscribe to this Journal Request Sample Copy Search Subject Related Journals Give us your comments Journal of Intelligent and Robotic Systems
19 (3):271-298, July 1997.
© Kluwer Academic Publishers

Sensor Fusion and Planning with Perception–Action Network

Sukhan Lee
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California 91109, U.S.A. Depts. of EE-Systems and CS, University of Southern California, Los Angeles, CA 90089-0781, U.S.A.

Abstract
Robot intelligence requires a real-time connection between sensing and action. A new computation principle of robotics that efficiently implements such a connection is utmost important for the new generation of robotics. In this paper, a perception–action network is presented as a means of efficiently integrating sensing, knowledge, and action for sensor fusion and planning. The network consists of a number of heterogeneous computational units, representing feature transformation and decision-making for action, which are interconnected as a dynamic system. New input stimuli to the network invoke the evolution of network states to a new equilibrium, through which a real-time integration of sensing, knowledge, and action can be accomplished. The network provides a formal, yet general and efficient, method of achieving sensor fusion and planning. This is because the uncertainties of signals, propagated in the network, can be controlled by modifying sensing parameters and robot actions. Algorithms for sensor planning based on the proposed network are established and applied to robot self-localization. Simulation and experimental results are shown.

Keywords
sensor fusion, planning, dynamic system, robotic system, uncertainty

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ISSN 0921-0296