TY - GEN
T1 - A spatial orientation and information system for indoor spatial awareness
AU - Li, Rongxing
AU - Skopljak, Boris
AU - He, Shaojun
AU - Tang, Pingbo
AU - Yilmaz, Alper
AU - Jiang, Jinwei
PY - 2010
Y1 - 2010
N2 - Timely and precision indoor spatial awareness is critical for a variety of facility management and building emergency response scenarios, such as facility manager navigation for regular building system maintenance, and firefighter navigation. Since indoor environments do not have GPS coverage and many indoor spaces have similar appearances, people under stress tend to lose their spatial awareness and have difficulty in analyzing their surroundings for completion of their tasks or finding a safe-haven. State-of-art indoor navigation solutions collectively use the magnetic field of the Earth, or deploy a wireless sensor network serving as spatial reference framework to achieve high precision localization. The magnetic field based approaches have decreased performance in areas with objects having strong magnetic fields, while the wireless sensor-network based approaches involve substantial investments into the wireless infrastructure. Moreover, complex indoor environments usually cause complicated interactions between the wireless sensors and the indoor objects, which pose additional technical challenges. The research presented in this paper explores an indoor navigation solution composed of passive sensors and uniquely integrates data acquired from an Inertial Measurement Unit (IMU), a camera system (vision sensor), and a step sensor for precision tracking of the trajectory of a user. Contrary to other methods, the proposed system does not rely on magnetic field sensing and a wireless sensor networks. The developed algorithms exploit the IMU signals for localization, the vision sensors for heading estimation and the step sensor for detecting stationary phases of the foot based. An Extended Kalman Filter (EKF) integrates this information and achieves disclosure error of 5% of tracking accuracy on average. Preliminary experimental results show the potential of this approach in urban setting.
AB - Timely and precision indoor spatial awareness is critical for a variety of facility management and building emergency response scenarios, such as facility manager navigation for regular building system maintenance, and firefighter navigation. Since indoor environments do not have GPS coverage and many indoor spaces have similar appearances, people under stress tend to lose their spatial awareness and have difficulty in analyzing their surroundings for completion of their tasks or finding a safe-haven. State-of-art indoor navigation solutions collectively use the magnetic field of the Earth, or deploy a wireless sensor network serving as spatial reference framework to achieve high precision localization. The magnetic field based approaches have decreased performance in areas with objects having strong magnetic fields, while the wireless sensor-network based approaches involve substantial investments into the wireless infrastructure. Moreover, complex indoor environments usually cause complicated interactions between the wireless sensors and the indoor objects, which pose additional technical challenges. The research presented in this paper explores an indoor navigation solution composed of passive sensors and uniquely integrates data acquired from an Inertial Measurement Unit (IMU), a camera system (vision sensor), and a step sensor for precision tracking of the trajectory of a user. Contrary to other methods, the proposed system does not rely on magnetic field sensing and a wireless sensor networks. The developed algorithms exploit the IMU signals for localization, the vision sensors for heading estimation and the step sensor for detecting stationary phases of the foot based. An Extended Kalman Filter (EKF) integrates this information and achieves disclosure error of 5% of tracking accuracy on average. Preliminary experimental results show the potential of this approach in urban setting.
KW - Extended kalman filter
KW - Information system
KW - Navigation
KW - Sensor network
KW - Spatial disorientation
UR - http://www.scopus.com/inward/record.url?scp=78650872703&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78650872703&partnerID=8YFLogxK
U2 - 10.1145/1865885.1865889
DO - 10.1145/1865885.1865889
M3 - Conference contribution
AN - SCOPUS:78650872703
SN - 9781450304337
T3 - ISA 2010 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
SP - 10
EP - 15
BT - ISA 2010 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness
T2 - 2nd International Workshop on Indoor Spatial Awareness, ISA 2010, in Conjunction with the 18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2010
Y2 - 2 November 2010 through 2 November 2010
ER -