Explore and Return: Experimental Validation of Real-Time Concurrent Mapping and Localization

This paper describes a real-time implementation of feature-based concurrent mapping and localization (CML) running on a mobile robot in a dynamic indoor environment. Novel characteristics of this work include: (1) a hierarchical representation of uncertain geometric relationships that extends the SPMap framework, (2) use of robust statistics to perform extraction of line segments from laser data in real-time, and (3) the integration of CML with a “roadmap” path planning method for autonomous trajectory execution. These innovations are combined to demonstrate the ability for a mobile robot to autonomously return back to its starting position within a few centimeters of precision, despite the presence of numerous people walking through the environment.