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Intelligent Control of Autonomous Six-Legged Robots by Neural Networks

  • Autonomous mobile six-legged robots are able to demonstrate the potential of intelligent control systems based on recurrent neural networks. The robots evaluate only two forward and two backward looking infrared sensor signals. Fast converging genetic training algorithms are applied to train the robots to move straight in six directions. The robots performed successfully within an obstacle environment and there could be observed a never trained useful interaction between each of the single robots. The paper describes the robot systems and presents the test results. Video clips are downloadable under www.inform.fh-hannover.de/download/lechner.php. Held on IFAC International Conference on Intelligent Control Systems and Signal Processing (ICONS 2003, April 2003, Portugal).

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Metadaten
Author:Werner Lechner, Frank Müller
URN:urn:nbn:de:bsz:960-opus-289
DOI:https://doi.org/10.25968/opus-103
Document Type:Conference Proceeding
Language:English
Year of Completion:2003
Publishing Institution:Hochschule Hannover
Release Date:2008/09/05
Tag:Articial intelligence; Genetic algorithms; Intelligent control; Neural controls; Neural networks; Neural-network models; Robotics
GND Keyword:Künstliche Intelligenz; Robotik; Neuronales Netz; Genetischer Algorithmus
Link to catalogue:599906375
Institutes:Fakultät IV - Wirtschaft und Informatik
DDC classes:004 Informatik
Licence (German):License LogoUrheberrechtlich geschützt