A pre-offering view system for teleoperators of heavy machines to acquire cognitive maps

Ryuya Sato*, Mitsuhiro Kamezaki, Satoshi Niuchi, Shigeki Sugano, Hiroyasu Iwata

*この研究の対応する著者

研究成果: Conference contribution

抄録

In teleoperation of heavy machines, work efficiency will be 50% lower than manned operation because operators cannot obtain effective information about work sites due to the limitation of current monitoring systems. Operators would have opportunities to obtain such information before work (about a week required to introduce teleoperation systems) and during work. As a fundamental study to support operator's spatial cognition, we developed views to provide spatial information of work sites before work. Humans have cognitive maps which are created based on knowledge acquired from survey and route perspectives. To make operators acquire the above two knowledge, we provide a bird's-eye view that can be changed by operators to acquire a knowledge from survey perspective, and a view from operator's viewpoint that can be changed by operator's intention to acquire a knowledge from route perspective. To evaluate two pre-offering views, we preformed experiments using a virtual reality simulator. The results indicated that a view to acquire a knowledge from survey perspective could help operators plan totally and one to acquire a knowledge from route perspective could help operators plan locally, and could increase work efficiency.

本文言語English
ホスト出版物のタイトルSSRR 2017 - 15th IEEE International Symposium on Safety, Security and Rescue Robotics, Conference
出版社Institute of Electrical and Electronics Engineers Inc.
ページ61-66
ページ数6
ISBN(電子版)9781538639221
DOI
出版ステータスPublished - 2017 10 26
イベント15th IEEE International Symposium on Safety, Security and Rescue Robotics, SSRR 2017 - Shanghai, China
継続期間: 2017 10 112017 10 13

出版物シリーズ

名前SSRR 2017 - 15th IEEE International Symposium on Safety, Security and Rescue Robotics, Conference

Other

Other15th IEEE International Symposium on Safety, Security and Rescue Robotics, SSRR 2017
国/地域China
CityShanghai
Period17/10/1117/10/13

ASJC Scopus subject areas

  • 人工知能
  • 安全性、リスク、信頼性、品質管理
  • 制御と最適化
  • 安全研究

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