Adaptation of orienting behavior: from the barn owl to a robotic system

Autonomous robotic systems need to adjust their sensorimotor coordinations so as to maintain good performance in the presence of changes in their sensory and motor characteristics. Biological systems are able to adapt to large variations in their physical and functional properties. In the last decade, the adjustment of orienting behavior has been carefully investigated in the barn owl, a nocturnal predator with highly developed auditory capabilities. We have recently proposed that the development and maintenance of the barn owl’s accurate orienting behavior can be explained through a process of learning based on the saliency of sensorimotor events. In this paper we consider the application of a detailed computer model of the principal neural structures involved in the process of spatial localization in the barn owl to the control of the orienting behavior of a robotic system, in the presence of auditory and visual stimulation. The system is composed of a robotic head equipped with two lateral microphones and a camera. We show that the model produces accurate orienting behavior toward both auditory and visual targets and is able to quickly recover good performance after alterations of the sensory inputs and motor outputs. The results illustrate that an architecture specifically designed to account for biological phenomena can produce flexible and robust motor control of a robotic system operating in the real world.