论文标题
Semrob：迈向机器人操作系统的语义流推理
SemRob: Towards Semantic Stream Reasoning for Robotic Operating Systems
论文作者
论文摘要
流处理和推理在物联网，工业物联网和智能城市等各种应用领域中引起了很大的关注。同时，基于推理和基于知识的特征吸引了对机器人技术的许多领域的研究，例如机器人映射，感知和互动。为此，语义流推理（SSR）框架可以将符号/语义流的表示形式与深神经网络统一，以将高维数据流（例如视频流和LiDar Point Clouds）与传统的图或关系流数据集成。因此，该定位和系统纸将概述我们在称为Semrob的机器人操作系统上促进语义流推理功能的平台的方法。
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.
