Abstract
Motivated by the need for assistance of indoor guidance for visually impaired persons (VIPs), a sensing system using inertial and geo-magnetic information has been developed to navigate a VIP person indoor. Orientation estimation, which is critical for indoor localization, is conducted using the information of the angular velocity, acceleration and geomagnetic field. By analyzing the characters of human gait, a method to eliminate the accumulated drift introduced by double integrations is introduced. By attaching the inertial sensor to the foot, the periodic stationary state will facilitate the drift correction. Also, the distinctive distortion of the geomagnetic field, which contains spatial information, provides a good approach to estimation location by utilizing an improved subsequence Dynamic Time Warping (DTW) Algorithm. To eliminate the effect of the relative constant geomagnetic field, magnetic tensor is introduced to extract the magnetic distortion. Kalman filter is utilized to fuse the orientation and location estimations of respective inertial and geomagnetic information and provide reliable and accurate indoor location. To demonstrate the accuracy and efficiency of the newly designed algorithms and sensing system, a prototype which consists of inertial sensors and magnetic tensor sensor was developed. Several experiments with three different indoor routes were designed to demonstrate and illustrate the sensing system
Advisor
Li Min
Committee Member
Ebrahimi Khosrow
Committee Member
Kuldeep Agarwal
Date of Degree
2020
Language
english
Document Type
Thesis
Degree
Master of Science (MS)
Department
Mechanical and Civil Engineering
College
Science, Engineering and Technology
Recommended Citation
Ammanabrolu, J. (2020). Indoor navigation for visually impaired person using inertial and geomagnetic information [Master’s thesis, Minnesota State University, Mankato]. Cornerstone: A Collection of Scholarly and Creative Works for Minnesota State University, Mankato. https://cornerstone.lib.mnsu.edu/etds/1049
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.