Urban Navigation with Semantic Maps
In a previous master’s thesis an autonomous robot was developed which is able to navigate in urban environments like campuses or city centers (see video). The navigation is based on a hierarchical map representation and path planning algorithm. In order to improve the navigation skills and the robustness of the robot in this master’s thesis the environment representation should be enriched with semantic information such as information about street crossings, pedestrian crossings or other important aspects. This information should be taken into account during navigation and the robot should automatically adapt its behavior according to that information, e.g. different motion pattern for pedestrian crossings.