Abstract

AbstractMotor synergies, i.e. systematic relations between effectors, have been first proposed as a principle in motor control by N. Bernstein in 1935. Thereafter, his idea has inspired many models of motor control in humans and animals. Recently, “linear synergy”, i.e. a linear relation between the torques applied to different joints, was reported to occur in human subjects during directional pointing movements [4]. In this paper, results from experiments in evolutionary robotics are presented to explore the concept of synergies in general and the role of linear synergy in the organisation of movement in particular. A 3D simulated robotic arm is evolved to reach to different target spots on a plane. Linear synergy is not found to be an outcome of the evolutionary search process, but imposing linear synergy as a constraint on artificial evolution dramatically improves evolvability and performance of evolved controllers.KeywordsEvolutionary SearchTarget SpotIncremental EvolutionEvolutionary RoboticPassive DynamicThese 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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