WEKO3
アイテム
A Comparative Analysis on Joint's Importance to Achieve Better Performance in Behavior Analysis in Human-Robot Collaborative Workspace
http://hdl.handle.net/10228/00009236
http://hdl.handle.net/10228/0000923697adc1ea-77fe-4da3-9a6e-8c95862485bc
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
LaSEINE-2021_064.pdf (3.5 MB)
|
|
| Item type | 会議発表論文 = Conference Paper(1) | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2023-05-08 | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| タイトル | ||||||||||||
| タイトル | A Comparative Analysis on Joint's Importance to Achieve Better Performance in Behavior Analysis in Human-Robot Collaborative Workspace | |||||||||||
| 言語 | en | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 著者 |
Nahid, Nazmun
× Nahid, Nazmun× 吉永, 章太朗× 井上, 創造
WEKO
27425
|
|||||||||||
| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | Manufacturing systems capable of performing multiple tasks require different types of resources. The fully automated system using robots has high speed, precision, tirelessness, and strength, but it is expensive whereas, human workers are smart, creative, flexible, and able to use different tools in different situations but do not have the same production ability as robots. Human-Robot Collaboration (HRC) thus becoming the new frontier in the research area as it allows us to combine the advantages of robots along with the adaptability and cognitive aptitudes of human workers. Though it has tremendous potential we failed to utilize it to the fullest due to safety concerns. In this work, we have presented a brief literature review regarding these issues. From our analysis, a simplified human motion analysis system is required especially where human and robot works within an intimate distance. So, we have done an elaborate comparative performance analysis on different body markers indicating different joints of the human body. We have found that in the case of close distance HRC the highest accuracy of 99 % is achieved from the Head-Wrist and the Shoulder-Wrist combination. Also, Head sensor data has a great impact in this type of scenario. | |||||||||||
| 備考 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | 3rd International Conference on Activity and Behavior Computing, ABC 2021, 22 October 2021 through 23 October 2021, Online | |||||||||||
| 書誌情報 |
発行日 2021-10-22 |
|||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
| 査読の有無 | ||||||||||||
| 値 | yes | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/140_ja.html | |||||||||||
| 論文ID（連携） | ||||||||||||
| 値 | 10403091 | |||||||||||
| 連携ID | ||||||||||||
| 値 | 10610 | |||||||||||
