A review of methodologies for natural-language-facilitated human–robot cooperation. (13th June 2019)

• Record Type: Journal Article
• Authors: Liu, Rui; Zhang, Xiaoli
• Is Part Of: International journal of advanced robotic systems. Volume 16:Number 3(2019:May/Jun.)
• Publication Date: 2019-06-13
• Subjects: Natural language -- human–robot cooperation -- NL instruction understanding -- NL-based execution plan generation -- knowledge-world mapping; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881419851402
• Languages: English
• ISSNs: 1729-8806

Abstract

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.