Tool-Use Model Considering Tool Selection by a Robot Using Deep Learning

Namiko Saito, Kitae Kim, Shingo Murata, Tetsuya Ogata, Shigeki Sugano

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a tool-use model that can select tools that require neither labeling nor modeling of the environment and actions. With this model, a robot can choose a tool by itself and perform the operation that matches a human command and the environmental situation. To realize this, we use deep learning to train sensory motor data recorded during tool selection and tool use as experienced by a robot. The experience includes two types of selection, namely according to function and according to size, thereby allowing the robot to handle both situations. For evaluation, the robot is required to generate motion either in an untrained situation or using an untrained tool. We confirm that the robot can choose and use a tool that is suitable for achieving the target task.

Original languageEnglish
Title of host publication2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018
PublisherIEEE Computer Society
Pages814-819
Number of pages6
ISBN (Electronic)9781538672839
DOIs
Publication statusPublished - 2019 Jan 23
Externally publishedYes
Event18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018 - Beijing, China
Duration: 2018 Nov 62018 Nov 9

Publication series

NameIEEE-RAS International Conference on Humanoid Robots
Volume2018-November
ISSN (Print)2164-0572
ISSN (Electronic)2164-0580

Conference

Conference18th IEEE-RAS International Conference on Humanoid Robots, Humanoids 2018
CountryChina
CityBeijing
Period18/11/618/11/9

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

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  • Cite this

    Saito, N., Kim, K., Murata, S., Ogata, T., & Sugano, S. (2019). Tool-Use Model Considering Tool Selection by a Robot Using Deep Learning. In 2018 IEEE-RAS 18th International Conference on Humanoid Robots, Humanoids 2018 (pp. 814-819). [8625048] (IEEE-RAS International Conference on Humanoid Robots; Vol. 2018-November). IEEE Computer Society. https://doi.org/10.1109/HUMANOIDS.2018.8625048