Robotic vision is concerned with providing, primarily through image sensory data acquisition and analysis, the basis for planning robotic manipulator actions upon and within a restricted world of solid objects. Ideally, its function should correspond to the human visual system's capacity to guide hand/eye coordination or body/eye navigation tasks. Fundamental to the notion of functionality in a 3D space partially filled with solid objects, is the requirement to appreciate the depth dimension, from a particular viewpoint. Human vision abounds with depth cues derivable from imagery and many of these have been the subjects of study for robotic vision application. However, direct range recovery using time-of-flight methods (ultrasonic or light) has distinct advantages for robotics and it is easy to justify these alternative approaches despite (and maybe even because of) their independence from visual cues.
This paper presents work in progress in the Computer Vision and Robotics Laboratory at The Australian National University towards implementing a robotic hand/eye coordination system with applicability in the scene domain of brightly coloured, simply shaped objects with relatively untextured surfaces in arbitrary 3 dimensional configurations. The advantages of using directly acquired range data (via a laser time-of-flight range scanner) in enhancing the scene segmentation phase of analysis is emphasised and fairly convincing results presented. Actual vision-driven manipulation has not yet been developed but plans towards this end are included.