Embodied Computer Vision For Mobile Robots

Nick Barnes and Zhi-Qiang Liu Computer Vision and Machine Intelligence Lab, Department of Computer Science, The University of Melbourne, Parkville, Victoria, 3052, AUSTRALIA Abstract | The basic idea that the perception of actual embodied beings, be they animal or robotic, is fundamentally related to their embodiment is generally referred to as Purposive or Animate Vision. Research in this eld generally emphasises low-level vision techniques. This paper outlines a philosophical basis for embodied perception, and develops a framework for conceptual embodiment of vision-guided robots. The aim is to facilitate the use of high-level vision through an active perception framework. We argue that the classical computer vision paradigm has problems in high-level vision due to an implicit assumption that objects in the world can be objectively subdivided into categories. Further, that through conceptual embodiment, active perception o ers a way forward. We present a mobile robot navigation system based on the principles of conceptual embodiment. The system uses object recognition to guide a robot around known objects. The robot's object model is embodied, and this embodiment yields speci c advantages for the robot.