An approach-path independent framework for place recognition and mobile robot localization in interior hallways

Our work provides a fast approach-path-independent framework for the problem of place recognition and robot localization in indoor environments. The approach-path independence is achieved by using highly viewpoint-invariant 3D junction features extracted from stereo pairs of images; these are based on stereo reconstructions of the JUDOCA junctions extracted from the individual images of a stereo pair. The speed in place-recognition and robot-localization is achieved by using a novel cylindrical data structure - we refer to it as the Feature Cylinder - for representing either all of the 3D junction features found in a hallway system during the learning phase of the robot or a set of locale signatures derived from the data. For the case when all data is placed on the Feature Cylinder, we can use the 3D-POLY polynomial-time in a hypothesize-and-verify approach to place recognition. On the other hand, in the locale signature based approach, we can use the same data structure for constant-time place recognition.