Work

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

Year: 2017

Type: article

Abstract: 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.

Source: IEEE Transactions on Neural Systems and Rehabilitation Engineering

DOI: 10.1109/tnsre.2017.2682265

Authors: He Zhang, Cang Ye

Institution: University of Arkansas at Little Rock

Language: English

Topic: Robotics and Sensor-Based Localization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Eye Institute, National Institute of Biomedical Imaging and Bioengineering