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移动机器人的改进无迹粒子滤波蒙特卡罗定位算法
  • ISSN号：0254-4156
  • 期刊名称：自动化学报
  • 时间：0
  • 页码：851-857
  • 语言：中文
  • 分类：TP277[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构：[1]清华大学智能技术与系统国家重点实验室,北京100084, [2]哈尔滨工业大学机器人技术与系统国家重点实验室,哈尔滨150080, [3]中国科学院自动化研究所,北京100190
  • 相关基金：国家高科术研究发展计划（863计划）（2007AA04Z232）; 国家自然科学基金（60909055 90820304）; 机器人技术与系统国家重点实验室开放研究项目（SKLRS-2009-ZD-04）; 中国博士后科学基金（20080440382）资助
  • 相关项目：智能控制理论
作者： 孙富春|宋宇|李庆玲|
关键词： 移动机器人, 蒙特卡罗定位, 粒子滤波, 无迹卡尔曼滤波, Mobile robot, Monte Carlo localization（MCL）, particle filter, unscented Kalman filter
中文摘要：

粒子滤波是移动机器人蒙特卡罗定位（Monte Carlo localization,MCL）的核心环节.首先,针对粒子滤波过程的粒子退化问题,利用迭代Sigma点卡尔曼滤波来精确设计粒子滤波器的提议分布,以迭代更新方式将当前观测信息融入顺序重要性采样过程,提出IUPF（Improved unscented particle filter）算法.然后,将IUPF与移动机器人MCL相结合,给出IUPF-MCL定位算法的实现细节.仿真结果表明,IUPF-MCL是一种精确鲁棒的移动机器人定位算法.

英文摘要：

Particle filter is a key issue in mobile robot Monte Carlo location（MCL）.Firstly,improved unscented particle filter（IUPF） algorithm is proposed in this paper.To overcome particles degeneracy phenomenon,the algorithm utilizes iterated sigma points Kalman filter to generate more accurate proposal distribution,which introduces most recent measurement information into sequential importance sampling（SIS） routine through iterated update processing.Secondly,by applying IUPF to MCL,IUPF-MCL algorithm is given.Finally,simulation results show that IUPF-MCL is an accurate and robust mobile robot localization algorithm.

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期刊信息
  • 《自动化学报》
  • 中国科技核心期刊
  • 主管单位:中国科学院
  • 主办单位:中国自动化学会 中国科学院自动化研究所
  • 主编：王飞跃
  • 地址：北京东黄城根北街16号
  • 邮编：100717
  • 邮箱：aas@ia.ac.cn
  • 电话：010-64019820
  • 国际标准刊号：ISSN：0254-4156
  • 国内统一刊号：ISSN：11-2109/TP
  • 邮发代号:2-180
  • 获奖情况:
  • 1997年获全国优秀期刊奖,1985、1990、1996、2000年获中国科学院优秀期刊二等奖,2002年获国家期刊奖
  • 国内外数据库收录:
  • 美国数学评论（网络版）,德国数学文摘,荷兰文摘与引文数据库,美国工程索引,日本日本科学技术振兴机构数据库,中国中国科技核心期刊,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）,中国北大核心期刊（2011版）,中国北大核心期刊（2014版）,中国北大核心期刊（2000版）
  • 被引量:27550