Sign detection for autonomous navigation

Abstract

Mobile robots currently cannot detect and read arbitrary signs. This is a major hindrance to mobile robot usability, since they cannot be tasked using directions that are intuitive to humans. It also limits their ability to report their position relative to intuitive landmarks. Other researchers have demonstrated some success on traffic sign recognition, but using template based methods limits the set of recognizable signs. There is a clear need for a sign detection and recognition system that can process a much wider variety of signs: traffic signs, street signs, store-name signs, building directories, room signs, etc. We are developing a system for Sign Understanding in Support of Autonomous Navigation (SUSAN), that detects signs from various cues common to most signs: vivid colors, compact shape, and text. We have demonstrated the feasibility of our approach on a variety of signs in both indoor and outdoor locations.