AfRob: The affordance network ontology for robots

Abstract

AfNet, The Affordance Network is an open affordance computing initiative that provides affordance knowledge ontologies for common household articles in terms of affordance features using surface forms termed as afbits (affordance bits). AfNet currently offers 68 base affordance features (25 structural, 10 material, 33 grasp), providing over 200 object category definitions in terms of 4000 afbits. Symbol grounding algorithms for these affordance features enable recognition of objects in visual (RGB-D) data. While AfNet is built as a generic visual knowledge ontology for recognition, it is well suited for deployment on domestic robots. In this paper, we describe AfRob, an extension of AfNet for robotic applications. AfRob builds upon AfNet by imbibing semantic context and mapping for holistic recognition and manipulation of objects in domestic environments. AfRob also offers modules to enable robots to interact and grasp objects through the generation of grasp affordances. The paper also details the inference mechanisms that adapt AfNet for robots in domestic contexts. Results demonstrate the efficiency of the affordance driven approach to holistic visual processing.