[3L4-GS-8] Robot and real worlds

[3L4-GS-8-05] Event-centric Knowledge Graph Representation to Transcribe Human Activity into the Cyber-Physical System

〇Ken FUKUDA¹, Shusaku Egami¹, Takanori Ugai^1,3, Takeshi Morita², Mikiko Oono¹, Kouji Kitamura¹, QIU YUE¹, Kensho Hara¹, Kouji Kozaki^1,4, Takahiro Kawamura^1,5 (1. AIST, 2. Aoyama Gakuin University, 3. Fujitsu Limited, 4. Osaka Electro-Communication University, 5. National Agriculture and Food Research Organization)

[[Online]]

Keywords:Cyber Physical System, Knowledge Graph, Human Activity Recognition, HRI, Event-centered System

Expectations are rising for human-centered AI embodied in the real world. Nevertheless, applications such as older adult support, child monitoring, and general-purpose robots for home use require event-centric knowledge of what happened in addition to observed data and external factual knowledge.

In previous work, we have modeled event-centric knowledge graphs for mystery novels, using events as units to represent the whole scene as a sequence of events. We have also developed VirtualHome2KG, representing human behavior in cyberspace as an event-centric knowledge graph, including living environments and furniture and rooms.
On the other hand, we are also developing an inference system that uses event-centric knowledge graphs to infer and explain dangers in daily life and derive safer alternatives.

In this study, we discuss the schema of event-centric knowledge graphs, which enables us to infer risks that are difficult to detect directly in daily life and improve planning accuracy for generous-purpose home robots.
Furthermore, we aim to emulate human daily living activity represented by knowledge graphs in cyberspace using VirtualHome2KG to provide a high-quality data set that serves to improve video recognition technology.