Development of a basic educational kit for robotic system with deep neural networks

Momomi Kanamura, Kanata Suzuki, Yuki Suga, Tetsuya Ogata*

*この研究の対応する著者

研究成果: Article査読

抄録

In many robotics studies, deep neural networks (DNNs) are being actively studied due to their good performance. However, existing robotic techniques and DNNs have not been systematically integrated, and packages for beginners are yet to be developed. In this study, we proposed a basic educational kit for robotic system development with DNNs. Our goal was to educate beginners in both robotics and machine learning, especially the use of DNNs. Initially, we required the kit to (1) be easy to understand, (2) employ experience-based learning, and (3) be applicable in many areas. To clarify the learning objectives and important parts of the basic educational kit, we analyzed the research and development (R&D) of DNNs and divided the process into three steps of data collection (DC), machine learning (ML), and task execution (TE). These steps were configured under a hierarchical system flow with the ability to be executed individually at the development stage. To evaluate the practicality of the proposed system flow, we implemented it for a physical robotic grasping system using robotics middleware. We also demonstrated that the proposed system can be effectively applied to other hardware, sensor inputs, and robot tasks.

本文言語English
論文番号3804
ジャーナルSensors
21
11
DOI
出版ステータスPublished - 2021 6 1

ASJC Scopus subject areas

  • 分析化学
  • 情報システム
  • 原子分子物理学および光学
  • 生化学
  • 器械工学
  • 電子工学および電気工学

フィンガープリント

「Development of a basic educational kit for robotic system with deep neural networks」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル