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The Role of Fuzzy Logic Control in Evolutionary Robotics

  • Frank Hoffmann
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 61)

Abstract

Traditional AI approaches decompose robotic behaviors into a sense-model-plan-act type of hierarchy. The sensors provide perceptual information, which is used to build a model of the current environment. The planner generates a plan that enables the robot to accomplish the given task. A controller executes the actions commanded by the planner without taking novel sensor information into account. The utility of this model-based reasoning approach for the design of intelligent robots is limited due to uncertainties inherent to unstructured environments, unreliable and incomplete perceptual information and imprecise actuators.

Keywords

Fuzzy Logic Mobile Robot Fuzzy Rule Fuzzy Controller Real Robot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Frank Hoffmann

There are no affiliations available

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