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  • 學位論文

使用慣性感測單元之室內及戶外行人航位推算法

Indoor/Outdoor Pedestrian Dead Reckoning Method Using IMU

指導教授 : 石勝文
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摘要


在本論文中,我們使用微機電系統 (Micro Electro Mechanical System) 技術製作出的慣性感測單元 (Inertial Measurement Unit) 來追蹤行人活動軌跡。微機電慣性感測單元是由三軸加速度計、三軸速度陀螺儀以及三軸磁力計組合而成,具有體積小、重量輕、成本低等特性。在本研究中,微機電慣性感測單元是安裝在受測者的鞋面上,以追蹤行人活動軌跡。論文中所提出來的方法是利用IMU結合粒子濾波器 (Particle Filter) 和自製地圖及Google戶外空照圖的方式,做出適用於室內及戶外的行人追蹤定位系統。在室內地圖中,我們利用不同顏色的像素值,區分出建築物中的障礙、通路、樓梯、以及出入口等不同部分,並用以防止粒子出現穿牆而過、跨越欄杆等不合理的行動路徑。於戶外地圖中,我們也標示出道路及建築物外牆及入口,以利正確追蹤。此外,也結合了 GPS (Global Positioning System) 的量測值,有效的降低粒子追蹤路線的偏移。於室內及戶外之間的轉換,透過影像中像素值的顏色變化達到地圖自動切換的效果,讓行人無論行走於室內或戶外都能夠被追蹤定位。由實驗結果顯示,被追蹤者的行動路徑在室內及戶外地圖上,都正確的行走在合理的範圍,達到行人追蹤定位的結果。

並列摘要


In this thesis, we use an inertial measurement unit (IMU) fabricated with the micro electro mechanical (MEMS) technique to study the pedestrian dead reckoning (PDR) problem. The IMU is composed of a 3-axis accelerometer, a 3-axis rate-gyro, and a 3-axis magnetometer, and is lightweight, miniature, and low cost due to the MEMS technique. In this work, the IMU is attached on the surface of the shoe tongue for trajectory tracking. The proposed method uses the particle filter, 2-D indoor/outdoor maps, and Google satellite images for indoor/outdoor PDR. In each indoor floor map, we use different colors to mark the walls, pillars, passageway, stairs, entrances and exits in order to eliminate unreasonable trajectories such as walking through a wall or a railing. Likewise, in the outdoor maps, roads, pathways, walls and the entrances of buildings are all marked clearly to facilitate accurate PDR computation. Also, we incorporate the global positioning system measurement to alleviate the trajectory drifting effectively. The color marks in the indoor/outdoor maps can also help us to determine the correct timing for changing a map to keep tracking a pedestrian walking in a mixed indoor/outdoor path. Experimental results show that the proposed method can provide accurate trajectory estimates in mixed indoor/outdoor paths.

參考文獻


[1] Y. S. Suh and S. Park, “Pedestrian inertial navigation with gait phase detection assisted zero velocity updating,” in Proceedings of the 4th International Conference on Autonomous Robots and Agents, (Wellington, New Zealand), pp. 336–341, 2 2009.
[2] A. Jimenez, F. Seco, J. Prieto, and J. G. C. Superior, “Indoor pedestrian navigation using an INS/EKF framework for yaw drift reduction and a foot-mounted IMU,” in Proceedings of 7th Workshop on Positioning Navigation and Communication, pp. 135–143, 3 2010.
[3] Y.-L. Hsu, “Bias compensation methods for pedestrian dead reckoning with a low-cost IMU,” Master’s thesis, National Chi Nan University, 2012.
[4] E. Foxlin, “Pedestrian tracking with shoe-mounted inertial sensors,” IEEE Computer Graphics and Applications, vol. 25, pp. 38–46, 11 2005.
[5] D. Torrieri, M. B. Bendak, and G. Ritchie, “Indoor geolocation by inertial navigation,” in Proceedings of Military Communications Conference, pp. 1760–1765, 2011.

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