지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
Recently, most of mobile devices are equipped with GNSS (Global Navigation Satellite System). When the GNSS signal is available, it is easy to obtain position information. However, GNSS is not suitable solution for indoor localization, since the signals are normally not reachable inside buildings. A wide varieties of technology have been developed as a solution for indoor localization such as Wi-Fi, beacons, and inertial sensor. With the increased sensor combinations in mobile devices, mobile devices also became feasible to provide a solution, which based on PDR (Pedestrian Dead Reckoning) method. In this study, we utilized the combination of three sensors equipped in mobile devices including accelerometer, digital compass, and gyroscope and applied three representative PDR methods. The proposed methods are done in three stages; step detection, step length estimation, and heading determination and the final indoor localization result was evaluated with terrestrial LiDAR (Light Detection And Ranging) data obtained in the same test site. By using terrestrial LiDAR data as reference ground truth for PDR in two differently designed experiments, the inaccuracy of PDR methods that could not be found by existing evaluation method could be revealed. The firstexperiment included extreme direction change and combined with similar pace size. Second experiment included smooth direction change and irregular step length. In using existing evaluation method which only checks traveled distance, The results of two experiments showed the mean percentage error of traveled distance estimation resulted from three different algorithms ranging from 0.028 % to 2.825% in the first experiment and 0.035% to 2.282% in second experiment, which makes it to be seen accurately estimated. However, by using the evaluation method utilizing terrestrial LiDAR data, the performance of PDR methods emerged to be inaccurate. In the firstexperiment, the RMSEs (Root Mean Square Errors) of x direction and y direction were 0.48 m and 0.41 m with combination of the best available algorithm. However, the RMSEs of x direction and y direction were 1.29 m and 3.13 m in the second experiment. The new evaluation result reveals that the PDR methods were not effective enough to find out exact pedestrian position information opposed to the result from existing evaluation method.
목차
Abstract
1. Introduction
2. Pedestrian Dead Reckoning
3. Experiment and Result
4. Conclusion
References
참고문헌 (9)
참고문헌 신청
Attia, M., Moussa, A., and El-Sheimy, N. (2013), Map aided pedestrian dead reckoning using buildings information for indoor navigation applications. Positioning, Vol. 4, No. 3, pp. 227-239.
FARO Technologies, Inc. (2018), FARO Focus 3D Laser Scanner, FARO Technologies UK Ltd, https://www.faro. com/en-gb/resource/faro-laser-scanner-focus3d-x-130- hdr/ (last date accessed: 21 October 2018).
Kim, J. W., Jang, H. J., Hwang, D. H., and Park, C. (2004), A step, stride and heading determination for the pedestrian navigation system. Journal of Global Position Systems, Vol. 3, No. 1-2, pp. 273-279.
Kim, J., and Lee, S. (2012), Sensor Information Filter for Enhancing the Indoor Pedestrian Localization Accuracy. Journal of Korea Robotics Society, Vol, 7, No. 4, pp. 276- 283. (in Korean with English abstract)
Kok, M., Hol, J. D., and Schon, T. B. (2017), Using Inertial Sensors for Position and Orientation Estimation, Foundations and Trends in Signal Processing, Vol. 11, No.1-2, pp 1-153.
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