SemRob：面向机器人操作系统的语义流推理
SemRob: Towards Semantic Stream Reasoning for Robotic Operating Systems
摘要：
流处理和推理在物联网、工业物联网和智慧城市等各种应用领域中得到了相当大的关注。与此同时，推理和基于知识的功能吸引了机器人许多领域的研究，如机器人映射，感知和交互。为此，语义流推理（SSR）框架可以将符号/语义流的表示与深度神经网络统一起来，以将高维数据流（如视频流和LiDAR点云）与传统的图形或关系流数据集成在一起。因此，这个定位和系统的文件将概述我们的方法来建立一个平台，以促进语义流推理功能的机器人操作系统称为SemRob。
英文摘要：
Stream processing and reasoning is getting considerable attention in various application domains such as IoT, Industry IoT and Smart Cities. In parallel, reasoning and knowledge-based features have attracted research into many areas of robotics, such as robotic mapping, perception and interaction. To this end, the Semantic Stream Reasoning (SSR) framework can unify the representations of symbolic/semantic streams with deep neural networks, to integrate high-dimensional data streams, such as video streams and LiDAR point clouds, with traditional graph or relational stream data. As such, this positioning and system paper will outline our approach to build a platform to facilitate semantic stream reasoning capabilities on a robotic operating system called SemRob.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
