Cubature MCL: Mobile Robot Monte Carlo Localization Based on Cubature Particle Filter

被引:0
作者
Li Qingling [1 ,2 ]
Song Yu [3 ]
机构
[1] China Univ Min & Technol, Sch Mech Elect & Informat Engn, Beijing 100083, Peoples R China
[2] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150080, Peoples R China
[3] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
来源
PROCEEDINGS OF THE 31ST CHINESE CONTROL CONFERENCE | 2012年
关键词
Mobile robot; Monte carlo localization; Particle filter; Gaussian weighted integral; Cubature rule;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Particle Filter is the key issue in mobile robot MCL (Monte Carlo Loclaization, MCL). To overcome particle set degeneracy phenomenon of the traditional MCL algorithm, a new Cubature MCL algorithm is proposed in this paper. The proposed Cubature MCL algorithm utilizes cubature kalman filter to generate more accuracy proposal distribution, which introduce most recent measurements into Sequential Importance Sampling (SIS) routine of the particle filter. The performance of the Cubature MCL algorithm is presented and analyzed in simulations. The results verify the effectiveness of the proposed Cubature MCL algorithm. The Cubature MCL provides a valuable reference for the mobile robot localization algorithm research.
引用
收藏
页码:5141 / 5145
页数:5
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