Bio-inspired Active Vision for Obstacle Avoidance

Abstract

Reliable distance estimation of objects in a visual scene is essential for any artificial vision system designed to serve as the main sensing unit on robotic platforms. This paper describes a vision-centric framework for a mobile robot which makes use of bio-inspired techniques to solve visual tasks, in particular to estimate disparity. Such framework features robustness to noise, high speed in data processing, good performance in 3D reconstruction, the possibility to orientate the cameras independently and it requires no explicit estimation of the extrinsic parameters of the cameras. These features permit navigation with obstacle avoidance allowing active exploration of the scene. Furthermore, the modular design allows the integration of new modules with more advanced functionalities.