Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot.

ABSTRACT: Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this st

SUBMITTER: Grinke E 

PROVIDER: S-EPMC4602151 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature