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Sensors 2013, 13(12), 15937-15953; doi:10.3390/s131215937

Autonomous Integrated Navigation for Indoor Robots Utilizing On-Line Iterated Extended Rauch-Tung-Striebel Smoothing

Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China
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Received: 24 September 2013 / Revised: 7 November 2013 / Accepted: 11 November 2013 / Published: 25 November 2013
(This article belongs to the Section Physical Sensors)
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Abstract

In order to reduce the estimated errors of the inertial navigation system (INS)/Wireless sensor network (WSN)-integrated navigation for mobile robots indoors, this work proposes an on-line iterated extended Rauch-Tung-Striebel smoothing (IERTSS) utilizing inertial measuring units (IMUs) and an ultrasonic positioning system. In this mode, an iterated Extended Kalman filter (IEKF) is used in forward data processing of the Extended Rauch-Tung-Striebel smoothing (ERTSS) to improve the accuracy of the filtering output for the smoother. Furthermore, in order to achieve the on-line smoothing, IERTSS is embedded into the average filter. For verification, a real indoor test has been done to assess the performance of the proposed method. The results show that the proposed method is effective in reducing the errors compared with the conventional schemes.
Keywords: inertial navigation systems (INS); integrated navigation; iterated extended Kalman filter (IEKF); extended Rauch-Tung-Striebel smoother (ERTSS); average filtering inertial navigation systems (INS); integrated navigation; iterated extended Kalman filter (IEKF); extended Rauch-Tung-Striebel smoother (ERTSS); average filtering
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Xu, Y.; Chen, X.; Li, Q. Autonomous Integrated Navigation for Indoor Robots Utilizing On-Line Iterated Extended Rauch-Tung-Striebel Smoothing. Sensors 2013, 13, 15937-15953.

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