Biokinematic study of barn owl head movements for the development of a bio-inspired active vision robotic system

Active vision is a process used by human beings and most animals to improve their visual recognition and avoid ill-posed visual problems. It has been proved that, by combining motion to their visual senses and perception, active observers can solve basic visual problems more efficiently than a passive one and that complex problems can also be addressed more easily. Autonomous robotic systems acting in dynamic environments should therefore imitate this process for a better image recognition and target tracking. Visually guided robotic systems also need to actively select visual information from the environment for detailed processing through mechanisms that mimic visual attention and saccadic eye movements. Developing and verifying computational models for visual search and implementing them on a robotic system are challenging important tasks that we will address based on our planned exploration of these mechanisms in the barn owl.We intend to investigate how, by imitating the barn owl’s repertoire of motor behaviors and search patterns, the autonomous agent could obtain meaningful information on the structure of the environment structure and possibly target position and motion. Towards that end, we have investigated the conspicuous head motions of barn owls and searched a kinematic characterization of the movements by means of screw theory.