Yingshen Zhao, Arkopaul Sarkar, Linda Elmhadhbi, Mohamed-Hedi Karray, P. Fillatreau, B. Archimède
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引用次数: 0
Abstract
Thanks to the advent of robotics in shopfloor and warehouse environments, control rooms need to seamlessly exchange information regarding the dynamically changing 3D environment to facilitate tasks and path planning for the robots. Adding to the complexity, this type of environment is heterogeneous as it includes both free space and various types of rigid bodies (equipment, materials, humans etc.). At the same time, 3D environment-related information is also required by the virtual applications (e.g., VR techniques) for the behavioral study of CAD-based product models or simulation of CNC operations. In past research, information models for such heterogeneous 3D environments are often built without ensuring connection among different levels of abstractions required for different applications. For addressing such multiple points of view and modelling requirements for 3D objects and environments, this paper proposes an ontology model that integrates the contextual, topologic, and geometric information of both the rigid bodies and the free space. The ontology provides an evolvable knowledge model that can support simulated task-related information in general. This ontology aims to greatly improve interoperability as a path planning system (e.g., robot) and will be able to deal with different applications by simply updating the contextual semantics related to some targeted application while keeping the geometric and topological models intact by leveraging the semantic link among the models.
由于机器人技术在车间和仓库环境中的应用,控制室需要无缝交换有关动态变化的 3D 环境的信息,以方便机器人执行任务和规划路径。由于这类环境既包括自由空间,也包括各种类型的刚体(设备、材料、人体等),因此更加复杂。同时,虚拟应用(如 VR 技术)在对基于 CAD 的产品模型进行行为研究或对数控操作进行仿真时,也需要与 3D 环境相关的信息。在过去的研究中,为这种异构三维环境建立的信息模型通常无法确保不同应用所需的不同抽象层次之间的联系。为满足三维物体和环境的多视角和建模要求,本文提出了一种本体模型,它集成了刚体和自由空间的上下文、拓扑和几何信息。本体提供了一个可演化的知识模型,可支持模拟任务相关的一般信息。本体旨在大大提高路径规划系统(如机器人)的互操作性,只需更新与某些目标应用相关的上下文语义,就能处理不同的应用,同时利用模型之间的语义联系,保持几何和拓扑模型的完整性。
Semantic WebCOMPUTER SCIENCE, ARTIFICIAL INTELLIGENCEC-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
8.30
自引率
6.70%
发文量
68
期刊介绍:
The journal Semantic Web – Interoperability, Usability, Applicability brings together researchers from various fields which share the vision and need for more effective and meaningful ways to share information across agents and services on the future internet and elsewhere. As such, Semantic Web technologies shall support the seamless integration of data, on-the-fly composition and interoperation of Web services, as well as more intuitive search engines. The semantics – or meaning – of information, however, cannot be defined without a context, which makes personalization, trust, and provenance core topics for Semantic Web research. New retrieval paradigms, user interfaces, and visualization techniques have to unleash the power of the Semantic Web and at the same time hide its complexity from the user. Based on this vision, the journal welcomes contributions ranging from theoretical and foundational research over methods and tools to descriptions of concrete ontologies and applications in all areas. We especially welcome papers which add a social, spatial, and temporal dimension to Semantic Web research, as well as application-oriented papers making use of formal semantics.