A review of methodologies for natural-language-facilitated human-robot cooperation

被引:24
|
作者
Liu, Rui [1 ]
Zhang, Xiaoli [2 ]
机构
[1] Carnegie Mellon Univ, RI, Pittsburgh, PA 15213 USA
[2] Colorado Sch Mines, IRSL, Golden, CO 80401 USA
来源
关键词
Natural language; human-robot cooperation; NL instruction understanding; NL-based execution plan generation; knowledge-world mapping; MODEL; RECOGNITION; COMMAND;
D O I
10.1177/1729881419851402
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Natural-language-facilitated human-robot cooperation refers to using natural language to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, natural-language-facilitated human-robot cooperation research has received increasing attention. Typical natural-language-facilitated human-robot cooperation scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, which can reveal latest methodologies of using natural language to facilitate human-robot cooperation, is missing. In this review, we comprehensively investigated natural-language-facilitated human-robot cooperation methodologies, by summarizing natural-language-facilitated human-robot cooperation research as three aspects (natural language instruction understanding, natural language-based execution plan generation, knowledge-world mapping). We also made in-depth analysis on theoretical methods, applications, and model advantages and disadvantages. Based on our paper review and perspective, future directions of natural-language-facilitated human-robot cooperation research were discussed.
引用
收藏
页数:17
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