Toward Robot Perception through Omnidirectional Vision

Vision is an extraordinarily powerful sense. The ability to perceive the environment allows for movement to be regulated by the world. Humans do this effortlessly but still lack the understanding of how perception works. In the case of visual perception, many researchers, from psychologists to engineers, are working on this complex problem. Our approach is to build artificial visual systems to examine how a robot can use images, which convey only 2D information, in a robust manner to drive its actions in 3D space. The perceptual capabilities we developed allowed our robot to undertake everyday navigation tasks, such as “go to the fourth office in the second corridor”. A critical component of any perceptual system, human or artificial, is the sensing modality used to obtain information about the environment. In the biological world, for example, one striking observation is the diversity of “ocular” geometries. The majority of insects and arthropods benefit from a wide field of view and their eyes have a spacevariant resolution. To some extent, the perceptual capabilities of these animals can be explained by their specially adapted eye geometries. Similarly, in this work, we explore the advantages of having large fields of view by using an omnidirectional camera with a 360◦ azimuthal field of view. Once images have been acquired by the omnidirectional camera, a question arises as to what to do with them. Should they form an internal representation of the world? Over time, can they provide intrinsic information about the world so as no representation is required? These fundamental questions have long been addressed by the computer vision community and go to the heart of our current understanding of visual perception. Before going on to detail our approach, a brief overview of this understanding will be provided.