A Review of Methodologies for Natural-Language-Facilitated Human-Robot Cooperation
📝 Abstract
Natural-language-facilitated human-robot cooperation (NLC) refers to using natural language (NL) to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, NLC research has received increasing attention. Typical NLC scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, that can reveal latest methodologies to use NL to facilitate human-robot cooperation, is missing. In this review, a comprehensive summary about methodologies for NLC is presented. NLC research includes three main research focuses: NL instruction understanding, NL-based execution plan generation, and knowledge-world mapping. In-depth analyses on theoretical methods, applications, and model advantages and disadvantages are made. Based on our paper review and perspective, potential research directions of NLC are summarized.
💡 Analysis
Natural-language-facilitated human-robot cooperation (NLC) refers to using natural language (NL) to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, NLC research has received increasing attention. Typical NLC scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, that can reveal latest methodologies to use NL to facilitate human-robot cooperation, is missing. In this review, a comprehensive summary about methodologies for NLC is presented. NLC research includes three main research focuses: NL instruction understanding, NL-based execution plan generation, and knowledge-world mapping. In-depth analyses on theoretical methods, applications, and model advantages and disadvantages are made. Based on our paper review and perspective, potential research directions of NLC are summarized.
📄 Content
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A Review of Methodologies for Natural- Language-Facilitated Human-Robot Cooperation Rui Liu, Xiaoli Zhang* Abstract- Natural-language-facilitated human-robot cooperation (NLC) refers to using natural language (NL) to facilitate interactive information sharing and task executions with a common goal constraint between robots and humans. Recently, NLC research has received increasing attention. Typical NLC scenarios include robotic daily assistance, robotic health caregiving, intelligent manufacturing, autonomous navigation, and robot social accompany. However, a thorough review, that can reveal latest methodologies to use NL to facilitate human-robot cooperation, is missing. In this review, a comprehensive summary about methodologies for NLC is presented. NLC research includes three main research focuses: NL instruction understanding, NL- based execution plan generation, and knowledge- world mapping. In-depth analyses on theoretical methods, applications, and model advantages and disadvantages are made. Based on our paper review and perspective, potential research directions of NLC are summarized. Index Terms- natural language, human-robot cooperation, NL instruction understanding, NL- based execution plan generation, knowledge-world mapping I. INTRODUCTION A. Background Attracted by the naturalness of natural language (NL) communications among humans, intelligent robots start to understand NL to develop intuitive human-robot cooperation in various task execution applications [1][2]. Natural-language-facilitated human-robot cooperation (NLC) has received increasing attention in human- involved intelligent robotics research over the recent decade. By using NL, human intelligence at high-level task planning and robot physical capability—such as force [3], precision [4], and speed [2]—at low-level task executions are combined to perform intuitive cooperation [5][6]. Due to the advantages of naturalness, information richness and standardized linguistic structures, NLC has been widely explored in areas, including daily assistance [5], medical caregiving [6][7], manufacturing [8], indoor or outdoor navigation [9], and social accompany [10]. Typical areas using NLC systems are shown in Fig. 1.
Fig. 1. Promising areas using natural-language-based human-robot cooperation. (a) is daily robotic assistance using NL [11]. A robot categorized daily objects with human NL instructions. (b) is autonomous manufacturing using NL [12]. An industrial robot welded parts with human’s oral requests. (c) is robotic navigation using NL [13]. A quadcopter navigated in indoor environments with human’s oral guidance. (d) is social accompany [14]. A pet dog is playing balls with a human with socialized verbal communications.
B. Motivation and systematic overview Advancements of NLP support an accurate understanding of the task in NLC. Advancement of a robot’s physical capability support increasingly improved task execution in NLC. With supporting technique from both NLP and robot execution, NLC has been developed from low-cognition-level symbol matching control, such as using “yes/no” to control robotic arms, to high-cognition-level task understanding, such as identifying a plan from the description “go straight and turn left at the second cross.” NLC research is regularly published in international journals, such as IJRR [15], TRO [16], AI [17] and KBS [18], and international conferences such as ICRA [19], IROS [20] and AAAI [21]. By using keywords ‘NLP, human, robot, cooperation, speech, dialog, natural language’, about 1200 papers were retrieved from Google Scholar [22], then with a focus of NL-facilitated human-robot cooperation, about 420 papers were finally kept. The publication trend is shown in Fig. 2, where the increasing significance of NLC is reflected by steadily increasing publication numbers. Compared with existing review papers about human- robot cooperation using communication manners such as gesture and pose [23][24], action and motion [25], and tactile [26], a review paper about NLC, which is human- robot cooperation using NL communication manner, is lacking. Given the huge potentials and increasingly received attention, it is necessary to make a summary of state-of-the-art NLC methodologies in wide-range
Rui Liu and Xiaoli Zhang are with the Intelligent Robotics and
Systems Lab (IRSL), Colorado School of Mines, Golden, CO 80401 USA. (e-mail:rliu@mines.edu, xlzhang@mines.edu.). *Corresponding author. cs.RO arXiv:1701.08756 2
domains, revealing current research progress and signposting future NLC research. The organization of this paper is shown in Fig. 3.
Fig. 2. The annual amount of NLC-related publications since the year 2000 according to our paper review. In the past 15 years, the number of NLC publications are steadily increasing and reaching a
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