Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques.

翻译：超声（US）因其无创、无辐射及实时成像优势，成为临床诊疗中运用最广泛的模态之一。然而，徒手超声检查高度依赖操作者经验。机器人超声系统（RUSS）旨在通过提供可重复性克服这一局限，同时提升操作灵巧性，并实现智能化的解剖结构与病变感知成像。除改善诊断效果外，RUSS还可为缺乏经验丰富的超声医师的人群提供医疗干预。本文将RUSS分为遥操作型和自主型两类进行系统分类。针对遥操作型RUSS，我们分别总结了其技术进展与临床评估结果。本综述重点聚焦自主机器人超声成像的最新研究成果，论证机器学习和人工智能作为核心技术，如何实现患者个性化、流程特异性、运动与形变感知的智能机器人图像采集。研究表明，面向自主RUSS的人工智能研究已推动学界深入理解并建模专家超声医师的语义推理与操作行为——我们将这一过程称为"超声语言"的复现。这一自主机器人超声采集研究的副产品，其价值与意义不亚于机器人超声检查技术本身所取得的突破。本文通过梳理底层技术，将为工程师与临床医生提供关于RUSS的全面认知。