Title :
Evolving morphology and control: A distributed approach
Author :
Mazzapioda, M. ; Cangelosi, A. ; Nolfi, S.
Author_Institution :
Inst. of Cognitive Sci. & Technol., Nat. Res. Council, Rome
Abstract :
In this paper we present a model which allows to co-evolve the morphology and the control system of realistically simulated robots (creatures). The method proposed is based on an artificial ontogenetic process in which the genotype does not specify directly the characteristics of the creatures but rather the growing rules that determine how an initial artificial embryo will develop on a fully formed individual. More specifically, the creatures are generated through a developmental process which occurs in time and space and which is realized through the progressive addition of both structural parts and regulatory substances which affect the successive course of the morphogenetic process. The creatures are provided with a distributed control system made up of several independent neural controllers embedded in the different body parts which only have access to local sensory information and which coordinate through the effects of physical actions mediated by the external environment through the emission/detection of signals which diffuse locally in space. The analysis of evolved creatures shows how they display effective morphology and control mechanisms which allow them to walk effectively and robustly both on regular and irregular terrains in all the replications of the experiment. Moreover, the obtained results show how the possibility to develop such skills can be improved by also selecting individuals on the basis of a task-independent component which reward them for the ability to coordinate the movements of their parts.
Keywords :
neurocontrollers; robots; artificial ontogenetic process; control system; distributed approach; evolving morphology; genotype; local sensory information; morphogenetic process; neural controllers; realistically simulated robots; Control system synthesis; Control systems; Distributed control; Embryo; Genetics; Manufacturing processes; Morphology; Orbital robotics; Robot kinematics; Signal detection;
Conference_Titel :
Evolutionary Computation, 2009. CEC '09. IEEE Congress on
Conference_Location :
Trondheim
Print_ISBN :
978-1-4244-2958-5
Electronic_ISBN :
978-1-4244-2959-2
DOI :
10.1109/CEC.2009.4983216