An IMU-Based Positioning System Using QR-Code Assisting for Indoor Navigation
In this paper, a positioning scheme combining inertial measurement unit (IMU) observation with QR code recognition is proposed to improve the location accuracy in an indoor environment. For the location-estimation technique, the proposed positioning schem
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Abstract In this paper, a positioning scheme combining inertial measurement unit (IMU) observation with QR code recognition is proposed to improve the location accuracy in an indoor environment. For the location-estimation technique, the proposed positioning scheme based on IMU observations is handled by the deadreckoning (DR) algorithm; in terms of a QR-code-assisted calibration technique, the proposed approach is an accuracy enhancement procedure that effectively reduces the error propagation caused by DR approach. Namely, with the assisting approach to recognize the locations of the QR-code-reference nodes as landmarks, a DR-based scheme using the landmark information can calibrate the estimated location, and then the error propagation effect is reduced. The experimental results demonstrate that the location based on the proposed approach have much lower location errors in an IMU positioning platform. As compared with the non-QRcode-assisted approach, the proposed algorithm can achieve reasonably good performance.
Keywords Dead reckoning Error propagation measurement unit QR code
Location estimation Inertial
Y.-S. Chiou F. Tsai Center for Space and Remote Sensing Research, National Central University, Jhongli, Taoyuan 32001, Taiwan e-mail: [email protected] F. Tsai e-mail: [email protected] S.-C. Yeh (&) W.-H. Hsu Department of Computer Science and Information Engineering, Ming Chuan University, Guishan, Taoyuan 33324, Taiwan e-mail: [email protected] W.-H. Hsu e-mail: [email protected]
S.-S. Yeo et al. (eds.), Computer Science and its Applications, Lecture Notes in Electrical Engineering 203, DOI: 10.1007/978-94-007-5699-1_66, Springer Science+Business Media Dordrecht 2012
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1 Introduction Location-aware services have received great attention for commercial, publicsafety, and military applications [1]. In the literatures, a number of positioning schemes have been reported [2]. There are two basic schemes applied in locationestimation systems. One is the radio ranging scheme (absolute scheme) based on wireless network services [2–5], the other is the speed sensing scheme (relative scheme) based on an inertial measurement unit (IMU), a package of inertial sensors (gyroscopes and accelerometers) [6, 7]. However, providing customers with tailored location-based services is a fundamental problem. Consequently, the fusion algorithm between the different devices is considered an important technique to improve location accuracy [8]. In addition, an accurate location can be improved with location tracking algorithms. The Kalman filtering algorithm is considered an optimal tracking algorithm for the linear Gaussian model [2–5]. Recently, for relative positioning scheme, a mobile terminal (MT) with low cost MEMS (micro-electro-mechanical systems) sensors, such as accelerometer, gyroscope, and compass, has made the dead-reckoning (DR) algorithm that becomes an attractive choice for indoor environment [6]. However, a magnetic compass does not functio
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