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