The contribution of active body movement to visual development in evolutionary robots

Abstract

Abstract-Inspired by the pioneering work by Held and Hein (1963) on the development of kitten visuo-motor systems, we explore the role of active body movement in the developmental process of the visual system by using robots. The receptive fields in an evolved mobile robot are developed during active or passive movement with a Hebbian learning rule. In accordance to experimental observations in kittens, we show that the receptive fields and behavior of the robot developed under active condition significantly differ from those developed under passive condition. A possible explanation of this difference is derived by correlating receptive field formation and behavioral performance in the two conditions. *

Robotics and Neuroscience

“…The authors concluded that correlated perception and motor actions are necessary for normal behavioural development, but could not precisely explain the mechanical cause. Suzuki, Floreano and Di Paolo [60] replicated those experiments with wheeled robots equipped with a pan-tilt camera and a neural network with Hebbian plasticity (a type of learning that involves strengthening synapses between co-activated neurons) linking the visual input to the motor commands of the camera and of the wheels. Constraints on body movements affected the development of visual receptive fields, which became responsive to sensory features that were correlated with the constrained behaviour and interfered with production of normal behaviour.…”

Evolution of Adaptive Behaviour in Robots by Means of Darwinian Selection

“…Current topics of biologically motivated research in evolutionary robotics include the role of ontogenetic development (e.g., [61]), the principles of neural control of highly dynamic and elastic body morphologies such as passive robotic walkers (e.g., [62],[63]), the functional role of morphology in coevolving bodies and brains [64], the role of active perception as a mean to structure and simplify sensory information in behaving organisms [65],[66], and the effects of synaptic plasticity [60],[67],[68] and neuromodulation [69] on organisms evolving in rapidly changing and partially unpredictable environments (i.e., under situations where individuals benefit to change behaviour over time). In particular, the incorporation of adaptive mechanisms during ontogeny mediated by phenotypic plasticity and learning (e.g., [70]) provides promising avenues for the study of processes operating at different spatial and temporal scales.…”

An evolutionary approach to road following: a simulated case study

“…The fitness function used in this approach is heavily inspired by that found in (Suzuki et al, 2005). This is a function which rewards forward progress of the robot, and is calculated and tallied at each time step based on the left (S l ) and right (S r ) wheel speeds, and the naïve straight-line distance reward applied at the end of the trial.…”