• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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A cascaded conditional random fields model of natural
 language processing for the navigation of rescue robots
 

WANG Heng-sheng1,2,LI Xi-yin2   

  1. (1.State Key Laboratory of High Performance Complex Manufacturing,Changsha 410083;
    2.College of Mechanical & Electrical Engineering,Central South University,Changsha 410083,China)
  • Received:2016-03-24 Revised:2016-05-03 Online:2017-08-25 Published:2017-08-25

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.

Key words: cascaded conditional random fields, natural language understanding, rescue robot navigation, human-robot interaction