Robot Navigation based on the Mapping of Coarse Qualitative Route Descriptions to Route Graphs

This paper describes the use of natural language route descriptions in the mobile robot navigation domain. Guided by corpus analysis and earlier work on coarse qualitative route descriptions, we decompose instructions given by humans into sequences of imprecise route segment descriptions. By applying fuzzy rules for the involved spatial relations and actions, we construct a search tree that can be searched in a depth-first branch-and-bound manner for the most probable goal configuration w.r.t. the global workspace knowledge of the robot. The applicability of our approach is shown by a real-world experiment where an operator instructs his automated wheelchair to navigate in an office-like environment