Embodied robots which can interact with their environment and neighbours are increasingly being used as a test case to develop Artificial Intelligence. This creates a need for multimodal robot controllers which can operate across different types of information including text. Large Language Models are able to process and generate textual as well as audiovisual data and, more recently, robot actions. Language Models are increasingly being applied to robotic systems; these Language-Based robots leverage the power of language models in a variety of ways. Additionally, the use of language opens up multiple forms of information exchange between members of a human-robot team. This survey motivates the use of language models in robotics, and then delineates works based on the part of the overall control flow in which language is incorporated. Language can be used by human to task a robot, by a robot to inform a human, between robots as a human-like communication medium, and internally for a robot's planning and control. Applications of language-based robots are explored, and finally numerous limitations and challenges are discussed to provide a summary of the development needed for language-based robotics moving forward. Links to each paper and, if available, source code are made available in the accompanying site at https://uos-haris.online/sooratilab/papers/WillSurvey/LangRobotSurvey.php

翻译：能够与环境及邻近个体交互的具身机器人正日益成为人工智能发展的重要测试平台。这催生了能够处理包括文本在内的多模态信息的机器人控制器需求。大语言模型已具备处理与生成文本、视听数据的能力，近期更扩展至机器人动作生成领域。语言模型在机器人系统中的运用日益广泛，这些基于语言的机器人以多种方式利用语言模型的强大能力。此外，语言的使用为人机团队成员之间开启了多元信息交互模式。本综述首先论证语言模型在机器人学中的应用价值，继而根据语言在整体控制流中的整合环节对现有研究进行系统分类：语言可被人类用于向机器人下达指令、被机器人用于向人类传递信息、作为类人通信媒介实现机器人间交互，以及支撑机器人内部的规划与控制。本文深入探讨了基于语言的机器人应用场景，最后通过剖析诸多局限性与挑战，为未来基于语言的机器人技术发展指明方向。各文献链接及源代码（若可用）可通过配套网站 https://uos-haris.online/sooratilab/papers/WillSurvey/LangRobotSurvey.php 获取。