论文标题

多代理人 - 机器人相互作用系统的调查

A Survey of Multi-Agent Human-Robot Interaction Systems

论文作者

Dahiya, Abhinav, Aroyo, Alexander M., Dautenhahn, Kerstin, Smith, Stephen L.

论文摘要

本文介绍了人类机器人相互作用(HRI)领域的文献调查,特别是包含两个以上试剂(即具有多个人类和/或多个机器人)的系统。我们确定了``多代理” HRI系统的三个核心方面,这些系统对于了解这些系统与二元系统以及彼此之间的不同有用。这些是团队结构,代理之间的互动风格以及系统的计算特征。在这些核心方面,我们介绍了HRI系统的五个属性。我们的另一个类别包括最近的文献中的示例,并分析了这些属性与二元人类机器人系统的案例不同,我们总结了当前文献的关键观察,并确定了在该领域的一部分,并确定了未来的研究。多机器人系统不仅需要几种代理之间的协调,还涉及多型和间接的互动,这些相互作用是二元组HRI系统中的多个代理。控制大量异质机器人和人类的HRI系统中的政策;

This article presents a survey of literature in the area of Human-Robot Interaction (HRI), specifically on systems containing more than two agents (i.e., having multiple humans and/or multiple robots). We identify three core aspects of ``Multi-agent" HRI systems that are useful for understanding how these systems differ from dyadic systems and from one another. These are the Team structure, Interaction style among agents, and the system's Computational characteristics. Under these core aspects, we present five attributes of HRI systems, namely Team size, Team composition, Interaction model, Communication modalities, and Robot control. These attributes are used to characterize and distinguish one system from another. We populate resulting categories with examples from recent literature along with a brief discussion of their applications and analyze how these attributes differ from the case of dyadic human-robot systems. We summarize key observations from the current literature, and identify challenges and promising areas for future research in this domain. In order to realize the vision of robots being part of the society and interacting seamlessly with humans, there is a need to expand research on multi-human -- multi-robot systems. Not only do these systems require coordination among several agents, they also involve multi-agent and indirect interactions which are absent from dyadic HRI systems. Adding multiple agents in HRI systems requires advanced interaction schemes, behavior understanding and control methods to allow natural interactions among humans and robots. In addition, research on human behavioral understanding in mixed human-robot teams also requires more attention. This will help formulate and implement effective robot control policies in HRI systems with large numbers of heterogeneous robots and humans; a team composition reflecting many real-world scenarios.

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