Towards Autonomous Wheelchair Systems in Urban Environments

In this paper, we explore the use of synthesized landmark maps for absolute localization of a smart wheelchair system outdoors. In this paradigm, three-dimensional map data are acquired by an automobile equipped with high precision inertial/GPS systems, in conjunction with light detection and ranging (LIDAR) systems, whose range measurements are subsequently registered to a global coordinate frame. The resulting map data are then synthesized a priori to identify robust, salient features for use as landmarks in localization. By leveraging such maps with landmark meta-data, robots possessing far lower cost sensor suites gain many of the benefits obtained from the higher fidelity sensors, but without the cost. We show that by using such a map-based localization approach, a smart wheelchair system outfitted only with a 2-D LIDAR and encoders was able to maintain accurate, global pose estimates outdoors over almost 1 km paths.