Mobile Robot Localization from Large-Scale Appearance Mosaics

Abstract

A new practical, high-performance mobile robot localization technique is described that is motivated by the fact that many man-made environments contain substantially flat, visually textured surfaces of persistent appearance. While the tracking of image regions is much studied in computer vision, appearance is still a largely unexploited localization resource in commercially relevant applications. We show how prior appearance models can be used to enable highly repeatable mobile robot guidance that, unlike commercial alternatives, is both infrastructure-free and free-ranging. Very large-scale mosaics are constructed and used to localize a mobile robot operating in the modeled environment. Straightforward techniques from vision-based localization and mosaicking are used to produce a field-relevant AGV guidance system based only on vision and odometry. The feasibility, design, implementation, and precommercial field qualification of such a guidance system are described.