DocumentCode :
1871634
Title :
Evolving sufficient robot controllers
Author :
Lund, Henrik Hautop ; Hallam, John
Author_Institution :
Dept. of Artificial Intelligence, Edinburgh Univ., UK
fYear :
1997
fDate :
13-16 Apr 1997
Firstpage :
495
Lastpage :
499
Abstract :
Different methods exist for reducing the time consumption in evolutionary robotics experiments. One is to use simulations, while another is to evolve controllers that are no more complex than task fulfilment requires. Behaviors such as exploration and homing, that seemingly demand a complex control system, only require a perceptron that connects a robot´s sensors to its motors. This is shown by evolving such neurocontrollers for the Khepera robot. An exploitation of the robot´s perception of the environment´s geometrical shape allows the robot to encode time, even though explicitly it is not presented with the time and there are no recurrent connections in the neurocontroller
Keywords :
genetic algorithms; mobile robots; neurocontrollers; optimal control; perceptrons; temporal reasoning; Khepera robot; environment geometrical shape perception; evolutionary robotics; exploration; homing; mobile robots; neurocontrollers; perceptron; robot sensor-motor connection; simulations; sufficient robot controllers; temporal encoding; time consumption; Artificial intelligence; Control systems; Convergence; HTML; Mobile robots; Neurocontrollers; Robot control; Robot sensing systems; Shape; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1997., IEEE International Conference on
Conference_Location :
Indianapolis, IN
Print_ISBN :
0-7803-3949-5
Type :
conf
DOI :
10.1109/ICEC.1997.592361
Filename :
592361
Link To Document :
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