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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.
Newman et al. (Wed,) studied this question.
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