On the perceptual advantages of visual suppression mechanisms for dynamic robot systems

The use of computer vision based methods to explore the surrounding environment and track individuals, is further enhanced by the ability to move the visual system, a process realized by biological organisms. However, several perceptual issues arise from the rapid movement of the image acquisition system: blurred images and visual-proprioceptive transient delays result in incorrect spatial location estimation. Inspired by the biological mechanism of saccadic suppression, our main contribution is a biologically inspired visual stability mechanism able to deal with problems arising from self-motion. Together with a state-of-the-art pedestrian detection algorithm, our proposed methodology contributes to enhancements in person position estimation, thus improving human-robot interaction behaviors.