Map generation for multiple image sensing sensor MISS under unknown robot egomotion

We design a new multiple image sensing sensor (MISS), which consists of a single camera and two different types of optics: an omnidirectional image sensor COPIS (conic projection image sensor) and binocular vision, for navigating the robot and understanding interesting objects in an environment by integrating both sensory data. Since COPIS observes a 360 degree view around the robot, it can observe global information of features (azimuths of vertical edges). On the other hand, binocular vision can obtain a sequence of stereo images although a field of view is limited by the visual angle of lens. In this paper, we integrate merits of omnidirectional vision and binocular vision, and propose an efficient sensing system for generating an environmental map by using MISS. Without an assumption of the exact known motion of the robot, MISS can generate an environmental map and estimate egomotion of the robot from both sensory information sources. In particular, the method is suitable for map generation during long robot movement because deadlocking error of the robot does not accumulate. The system has been evaluated on a prototype of MISS in a real environment