Integrating Multiple Representations of Spatial Knowledge for Mapping, Navigation, and Communication (2007)
A robotic chauffeur should reason about spatial information with a variety of scales, dimensions, and ontologies. Rich representations of both the quantitative and qualitative characteristics of space not only enable robust navigation behavior, but also permit natural communication with a human passenger. We apply a hierarchical framework of spatial knowledge inspired by human cognitive abilities, the Hybrid Spatial Semantic Hierarchy, to common navigation tasks: safe motion, localization, map-building, and route planning. We also discuss the straightforward mapping between the variety of ways in which people communicate with a chauffeur and the framework's heterogeneous concepts of spatial knowledge. We present pilot experiments with a virtual chauffeur.
In AAAI Spring Symposium Series, Interaction Challenges for Intelligent Assistants 2007. AAAI Technical Report SS-07-04.

Patrick Beeson Postdoctoral Alumni pbeeson [at] traclabs com
Benjamin Kuipers Formerly affiliated Faculty kuipers [at] cs utexas edu
Matt MacMahon Ph.D. Alumni adastra [at] cs utexas edu
Joseph Modayil Ph.D. Alumni modayil [at] cs utexas edu
Aniket Murarka Ph.D. Alumni aniket [at] cs utexas edu