Review on the Knowledge Graph in Robotics Domain

DOI

10.2991/iccia-19.2019.65How to use a DOI?

Keywords

Knowledge Graph; Knowledge Sharing; Knowledge representation; Knowledge Update.

Abstract

With the development of Artificial Intelligence technology, the application of robots in production and life is more and more extensive. How to improve the autonomy of robots and make robots complete tasks more accurately and quickly become a new research topic. One of the most important key tools which enable the robots to work more autonomously is knowledge. Robots need the relevant knowledge of environment, tasks, action and robot’s own abilities when perform a task. How to represent and organize the vast amount of knowledge and the complex relationships between these knowledges in a more effective way, so that the robot can retrieve relevant knowledge faster and conveniently, and reasoning based on the original knowledge to help the robot complete the task automatically, has been a new research problem. Subsequently, the concept of knowledge graph was proposed, and with its strong knowledge representation and organization ability, it has been widely studied in many domains. This paper mainly reviews the research status of knowledge graph of robotics domain, introduces several existing knowledge graphs, and compares and analyzes them in the aspect of knowledge representation, knowledge update, knowledge query and reasoning. Finally, we propose the shortage of the exiting knowledge graph and look forward to the future works.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Shuai Wang
AU  - Yu Zhang
AU  - Zhiyong Liao
PY  - 2019/07
DA  - 2019/07
TI  - Review on the Knowledge Graph in Robotics Domain
BT  - Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
PB  - Atlantis Press
SP  - 424
EP  - 431
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-19.2019.65
DO  - 10.2991/iccia-19.2019.65
ID  - Wang2019/07
ER  -