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並列摘要


The Kinect sensor has gained popularity in a large number of applications beyond its intended original design of being a 3D human interface device, including indoor navigation of pushcart and backpack sensor platforms. In this study, a performance analysis is provided based on a series of indoor tests, where sufficient control was available. This investigation aims at estimating and evaluating the total error budget of the trajectory recovery process that is based on using both optical (2D) and depth (3D) imagery. The sensor error budget defines a lower error bound for the trajectory estimation errors, i.e. what can be achieved under ideal conditions. The total error budget includes the object space dependency, the error introduced by the scene content in terms of geometry and texture that can be exploited to identify matching features in the image sequence. While it is difficult to encapsulate the impact of the object space in a rigorous sense, tendencies can be identified based on statistical evaluation of data acquired under typical object space scenarios. The test data used in this study was acquired at the Department of Civil, Environmental and Geodetic Engineering of the Ohio State University, using the updated prototype of the personal navigator developed earlier at the OSU Satellite Positioning and Inertial Navigation Laboratory (SPIN) Laboratory.

參考文獻


Kourogi, M., Sakata, N., Okuma, T., and Kurata, T., “Indoor/Outdoor Pedestrian Navigation with an Embedded GPS/RFID/Self-contained Sensor System,” Proceedings of 16th International Conference on Artificial Reality and Telexistence (ICAT2006), Hangzhou, China, September 2006, pp. 1310-1321.
Durrant-Whyte, H. and Bailey, T., “Simultaneous Localization and Mapping (SLAM): Part I The Essential Algorithms,” Robotics and Automation Magazine, Vol. 13, No. 2, 2006, pp. 99-110.
Veth, M. and Raquet, J., “Fusing Low-Cost Image and Inertial Sensors for Passive Navigation, NAVIGATION,” Journal of the Institute of Navigation, Vol. 54, No. 1, 2007, pp. 11-20.
Moafipoor, S., Grejner-Brzezinska, D. A., and Toth, C. K., A Fuzzy Dead Reckoning Algorithm for a Personal Navigator, Navigation, Winter 2008.
Weinmann, M., Wursthorn, S., and Jutzi, B., “Semi-automatic image-based co-registration of range imaging data with different characteristics,” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 38-3/W22, 2011, pp. 119-124.

被引用紀錄


Lin, Y. T. (2015). 建模與定量麻醉心電訊號裡的節律與非節律現象 [doctoral dissertation, National Taiwan University]. Airiti Library. https://doi.org/10.6342/NTU.2015.02479
Ho, P. F. (2016). 無線車載安全技術研究 [doctoral dissertation, National Chiao Tung University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0030-0803201714373390

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