Mobile robot navigation in enclosed large-scale space

We investigate the feasibility of construction of a landmark-based cognitive map, whose elements are the obstacles perceived by a robotic vehicle during exploration of an unknown, large-scale environment. This cognitive map can then be used as an aid for goal-oriented navigation in such a challenging environment. A map construction algorithm is described suitable for a mobile robot with the ability of temporarily marking a single location in an enclosed environment containing polygonal objects. The algorithm is being verified with a LEGO-Technic-based autonomous vehicle, equipped with a 2-DOF arm and relying on inaccurate odometric and short-range proximity sensing. The vehicle experimentally demonstrated skills including pick-and-place of a portable marker obstacle detection, as well as characterization and recognition of polygonal objects. These skills in conjunction with the approximate odometric measurements collected by the vehicle, also represent the repertoire of behaviors exploited in map-assisted navigation