计算机工程与科学2017，Vol.39Issue(8)：1538-1545,8.DOI:10.3969/j.issn.1007-130X.2017.08.024
机器人自然语言导航的层叠式条件随机场模型
A cascaded conditional random fields model of natural language processing for the navigation of rescue robots
摘要
Abstract
We propose a new method for rescue robots to understand navigation commands in Chinese natural language based on cascaded conditional random fields (CRFs).It consists of three layers of CRFs.The first layer is to tag the navigation part of speech (NPOS) using features from words,parts of speech and the context.The second layer is to extract basic navigation procedures (NPs) using features from words,NPOS labels and the context.The third layer is to recognize start places and end places of each NP using features from words,NPOS labels,NP labels and the context.Eventually,according to the relationship between the NPOSs and navigation elements,navigation information can be obtained from the navigation commands.The method can process navigation commands of uncontrolled natural language and the accuracy is 78.6 ％.It does not depend on custom-made instructions or maps,which is significant for rescue robot navigation through human-robot interaction.关键词
层叠条件随机场/自然语言理解/救灾机器人导航/人机交互Key words
cascaded conditional random fields/natural language understanding/rescue robot navigation/human-robot interaction分类
信息技术与安全科学引用本文复制引用
王恒升,李熙印..机器人自然语言导航的层叠式条件随机场模型[J].计算机工程与科学,2017,39(8):1538-1545,8.基金项目
国家“973”计划(2013CB035504) （2013CB035504）
