Research on Simultaneous Localization, Calibration and Mapping of Network Robot System

被引:1
|
作者
Wu, Peiliang [1 ]
Kong, Lingfu [1 ]
Kong, Liang [1 ]
Zhang, Shihui [1 ]
机构
[1] Yanshan Univ, Sch Informat Sci & Engn, 438 Hebei Ave, Qinhuangdao 066004, Hebei Province, Peoples R China
基金
中国国家自然科学基金;
关键词
network robot system; simultaneous localization; calibration and mapping; Rao-Blackwellized particle filtering; unscented transformation; CAMERA;
D O I
10.7305/automatika.2016.01.710
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a network robot system, a robot and a sensor network are integrated smoothly to develop their advantages and benefit from each other. Robot localization, sensor network calibration and environment mapping are three coupled issues to be solved once network robot system is introduced into a service environment. In this article, the problem of simultaneous localization, calibration and mapping is raised in order to improve their precision. The coupled relations among localization, calibration and mapping are denoted as a joint conditional distribution and then decomposed into three separate analytic terms according to Bayesian and Markov properties. The framework of Rao-Blackwellized particle filtering is used to solve the three analytic terms, in which extended particle filter is used for localization and unscented Kalman filter is used for both calibration and mapping. Simulations have been performed to demonstrate the validity and efficiency of the proposed solutions.
引用
收藏
页码:466 / 477
页数:12
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