Paper ID: 2201.11625

SemRob: Towards Semantic Stream Reasoning for Robotic Operating Systems

Manh Nguyen-Duc, Anh Le-Tuan, Manfred Hauswirth, David Bowden, Danh Le-Phuoc

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.

Submitted: Jan 27, 2022