Cooperative simultaneous localization and mapping algorithm based on distributed particle filter

被引：11
|
作者：
Wen, Shuhuan [1 ,2 ]
Chen, Jian [1 ,2 ]
Lv, Xiaohan [1 ,2 ]
Tong, Yongzheng [1 ,2 ]
机构：
[1] Yanshan Univ, Key Lab Ind Comp Control Engn Hebei Prov, Qinhuangdao, Peoples R China
[2] Yanshan Univ, Sch Elect Engn, Qinhuangdao, Peoples R China
来源：
INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS | 2019年 / 16卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Particle filter; simultaneous localization and mapping; distributed system; multiple robots;
D O I：
10.1177/1729881418819950
中图分类号：
TP24 [机器人技术];
学科分类号：
080202 ; 1405 ;
摘要：
In this article, cooperative simultaneous localization and mapping algorithm based on distributed particle filter is proposed for multi-robot cooperative simultaneous localization and mapping system. First, a multi-robot cooperative simultaneous localization and mapping system model is established based on Rao-Blackwellised particle filter and simultaneous localization and mapping (FastSLAM 2.0) algorithm, and an median of the local posterior probability (MP)-cooperative simultaneous localization and mapping algorithm combined with the M-posterior distributed estimation algorithm is proposed. Then, according to the accuracy advantage of the early landmarks comparing to the later landmarks in the simultaneous localization and mapping task, an improved time-median of the local posterior probability (MP)-cooperative simultaneous localization and mapping algorithm based on time difference optimization is proposed, which optimizes the weights of the local estimation and improves the accuracy of the global estimation. The simulation results show that the algorithm is practical and effective.
引用
收藏
页数：8
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