Evolutionary Robotics: The Biology,Intelligence,and Technology
Evolutionary Robotics: The Biology,Intelligence,and Technology
IEEE Spectrum - Modular robots change shape to conquer tasks and tough terrain
Self-organizing sync in a robotic swarm: a dynamical system view
IEEE Transactions on Evolutionary Computation
Software evolution of a hexapod robot walking gait
International Journal of Intelligent Systems Technologies and Applications
Evolving morphology and control: a distributed approach
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Taming the beast: guided self-organization of behavior in autonomous robots
SAB'10 Proceedings of the 11th international conference on Simulation of adaptive behavior: from animals to animats
Towards artificial evolution of complex behaviors observed in insect colonies
EPIA'11 Proceedings of the 15th Portugese conference on Progress in artificial intelligence
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In this paper we present a distributed control architecture for a simulated hexapod robot with twelve degrees of freedom consisting of six homogeneous neural modules controlling the six corresponding legs that only have access to local sensory information and that coordinate by exchanging signals that diffuse in space like gaseous neuro-trasmitters The free parameters of the neural modules are evolved and are selected on the basis of the distance travelled by the robot Obtained results indicate how the six neural controllers are able to coordinate so to produce an effective walking behaviour and to adapt on the fly by selecting the gait that is most appropriate to the current robot/environmental circumstances The analysis of the evolved neural controllers indicates that the six neural controllers synchronize and converge on an appropriate gait on the basis of extremely simple control mechanisms and that the effects of the physical interaction with the environment are exploited to coordinate and to converge on a tripod or tetrapod gait on the basis of the current circumstances.