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This model aims to facilitate collaboration by structuring information in a way that ensures semantic interoperability. The paper outlines the model's development process, beginning with a structured consolidation of information from pertinent scientific literature, resulting in a foundational framework for representing knowledge and semantics within the domain of AMRs. The practical application of the information model is demonstrated through a use case involving multiple AMRs. Additionally, the paper provides insights into the employed methodology, emphasizing the significance of systematic literature reviews and collaboration with practitioners to refine and validate the model. It also discusses theoretical and practical implications, addressing potential limitations encountered during the research.</p>","PeriodicalId":54794,"journal":{"name":"Journal of Intelligent & Robotic Systems","volume":"20 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards Semantic Interoperability: An Information Model for Autonomous Mobile Robots\",\"authors\":\"Marvin Zager, Christoph Sieber, Alexander Fay\",\"doi\":\"10.1007/s10846-024-02159-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The collaboration among autonomous mobile robots (AMRs), including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and/or unmanned surface vehicles (USVs), significantly enhances their capabilities by enabling them to tackle more complex tasks exceeding those of individual robots. However, to fully exploit this collaboration, a common understanding of exchanged information—referred to as semantic interoperability—is crucial. Achieving semantic interoperability between these robots requires a deep understanding of relevant information and its underlying structure. To address this challenge, this paper presents a platform- and technology-independent information model developed specifically for AMRs. This model aims to facilitate collaboration by structuring information in a way that ensures semantic interoperability. The paper outlines the model's development process, beginning with a structured consolidation of information from pertinent scientific literature, resulting in a foundational framework for representing knowledge and semantics within the domain of AMRs. The practical application of the information model is demonstrated through a use case involving multiple AMRs. 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引用次数: 0
摘要
自主移动机器人(AMR)包括无人驾驶飞行器(UAV)、无人驾驶地面飞行器(UGV)和/或无人驾驶水面飞行器(USV),这些机器人之间的协作使它们能够处理比单个机器人更复杂的任务,从而大大增强了它们的能力。然而,要充分利用这种协作,对所交换信息的共同理解(即语义互操作性)至关重要。要实现这些机器人之间的语义互操作性,需要深入了解相关信息及其底层结构。为了应对这一挑战,本文介绍了一种专门为 AMR 开发的、与平台和技术无关的信息模型。该模型旨在通过以确保语义互操作性的方式构建信息来促进协作。本文概述了该模型的开发过程,首先对相关科学文献中的信息进行了结构化整合,最终形成了一个用于表示 AMR 领域中的知识和语义的基础框架。通过一个涉及多个 AMR 的使用案例,展示了该信息模型的实际应用。此外,论文还对所采用的方法提出了见解,强调了系统性文献综述以及与从业人员合作完善和验证模型的重要性。论文还讨论了理论和实践意义,解决了研究过程中遇到的潜在限制。
Towards Semantic Interoperability: An Information Model for Autonomous Mobile Robots
The collaboration among autonomous mobile robots (AMRs), including unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and/or unmanned surface vehicles (USVs), significantly enhances their capabilities by enabling them to tackle more complex tasks exceeding those of individual robots. However, to fully exploit this collaboration, a common understanding of exchanged information—referred to as semantic interoperability—is crucial. Achieving semantic interoperability between these robots requires a deep understanding of relevant information and its underlying structure. To address this challenge, this paper presents a platform- and technology-independent information model developed specifically for AMRs. This model aims to facilitate collaboration by structuring information in a way that ensures semantic interoperability. The paper outlines the model's development process, beginning with a structured consolidation of information from pertinent scientific literature, resulting in a foundational framework for representing knowledge and semantics within the domain of AMRs. The practical application of the information model is demonstrated through a use case involving multiple AMRs. Additionally, the paper provides insights into the employed methodology, emphasizing the significance of systematic literature reviews and collaboration with practitioners to refine and validate the model. It also discusses theoretical and practical implications, addressing potential limitations encountered during the research.
期刊介绍:
The Journal of Intelligent and Robotic Systems bridges the gap between theory and practice in all areas of intelligent systems and robotics. It publishes original, peer reviewed contributions from initial concept and theory to prototyping to final product development and commercialization.
On the theoretical side, the journal features papers focusing on intelligent systems engineering, distributed intelligence systems, multi-level systems, intelligent control, multi-robot systems, cooperation and coordination of unmanned vehicle systems, etc.
On the application side, the journal emphasizes autonomous systems, industrial robotic systems, multi-robot systems, aerial vehicles, mobile robot platforms, underwater robots, sensors, sensor-fusion, and sensor-based control. Readers will also find papers on real applications of intelligent and robotic systems (e.g., mechatronics, manufacturing, biomedical, underwater, humanoid, mobile/legged robot and space applications, etc.).