A multiple model which is suitable for indoor and outdoor application is presented based on loca-lization algorithm. Due to big difference between indoor and outdoor environments, there hardly exists a general localization algorithm for the two environments. In this work, a switched scheme is proposed to deal with this problem. Because of nonlinearity in measurement, method based on particle filtering is adopted for the mode matching filter. In time update, movement between two consecutive frames is provided by an inertial measurement unit (IMU). In measurement update, global positioning system (GPS) and iBeacon are used as observers in outdoor and indoor, respectively. A weighted error compression ratio which can adjust Markovian parameters online is proposed to deal with mismatch of competition model resulted by model switching frequently. Thus the localization precision can be guaranteed in situation of frequent switch between indoor and outdoor. Experimental results demonstrate precision and robustness of the proposed method which outperforms some state-of-the-art methods (e.g., IMM-PF, single model algorithm, IMM-KF, etc), especially when observation noise exists.
ZHAO Guoqia,b,YANG Minga,b,WANG Binga,b,WANG Chunxiangc
. Mobile Robot Seamless Localization Based on Smart Device in Indoor and Outdoor Environments[J]. Journal of Shanghai Jiaotong University, 2018
, 52(1)
: 13
-19
.
DOI: 10.16183/j.cnki.jsjtu.2018.01.003
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