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.
翻译:溪流处理和推理正在诸如IoT、工业IoT和智能城市等各种应用领域引起相当重视。平行地,推理和知识性特征吸引了对机器人许多领域的研究,例如机器人绘图、认知和互动。为此,语管流推理(SSR)框架可以将象征/河流的表述与深神经网络统一起来,将高维数据流(如视频流和LIDAR点云)与传统图表或相关流数据整合起来。因此,本定位和系统文件将概述我们如何建立一个平台,以促进称为SemRob的机器人操作系统上的语系流推理能力。