An Indoor Wayfinding System Based on Geometric Features Aided Graph SLAM for the Visually Impaired

This paper presents a 6-degree of freedom (DOF) pose estimation (PE) method and an indoor wayfinding system based on the method for the visually impaired. The PE method involves two-graph simultaneous localization and mapping (SLAM) processes to reduce the accumulative pose error of the device. In the first step, the floor plane is extracted from the 3-D camera’s point cloud and added as a landmark node into the graph for 6-DOF SLAM to reduce roll, pitch, and
${Z}$
errors. In the second step, the wall lines are extracted and incorporated into the graph for 3-DOF SLAM to reduce
${X}$
,
${Y}$
, and yaw errors. The method reduces the 6-DOF pose error and results in more accurate pose with less computational time than the state-of-the-art planar SLAM methods. Based on the PE method, a wayfinding system is developed for navigating a visually impaired person in an indoor environment. The system uses the estimated pose and floor plan to locate the device user in a building and guides the user by announcing the points of interest and navigational commands through a speech interface. Experimental results validate the effectiveness of the PE method and demonstrate that the system may substantially ease an indoor navigation task.