| アイテムタイプ |
共通アイテムタイプ(1) |
| 公開日 |
2025-02-13 |
| タイトル |
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タイトル |
Solution of World Robot Challenge 2020 Partner Robot Challenge (Real Space) |
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言語 |
en |
| 著者 |
Ono, Tomohiro
Kanaoka, Daiju
Shiba, Tomoya
Tokuno, Shoshi
Yano, Yuga
Mizutani, Akinobu
Matsumoto, Ikuya
Amano, Hayato
田向, 権
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| 著作権関連情報 |
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権利情報 |
Copyright (c) 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group |
| 著作権関連情報 |
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|
権利情報Resource |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
権利情報 |
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. |
| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
The World Robot Challenge is an international competition for the social implementation of robots. Among them, the Partner Robot Challenge (Real Space) is a category that focuses on domestic service robots, competing to achieve simple tasks such as tidying a room, avoiding small obstacles, grasping a specified object from the shelf, and delivering an object to a waving person. In this category, we focused on the theme of ‘Keep Moving’ and worked on researching and developing technologies for object recognition, grasping, and other tasks. For object recognition, we propose an automatic dataset generator using a physics simulator and generate about 490,000 images in two hours. We trained it with an instance segmentation model, achieving an accuracy of about 79.3% in all games. For object grasping, we installed a three-dimensional sensor on the robot hand, and achieved successful grasping with high accuracy of about 79.6% (88.9% excluding failures due to hardware problems) in all games. In addition, we propose a motion synthesis method that simultaneously performs movement and posture transition to achieve high-speed motion. When navigation is executed, the robot changes to the navigation posture while aiming for the goal. Before reaching the goal, it changes the posture for the following action. As a result, we realized a speedup of about 1.32 times in the pick-and-place task. In the tidy-up task, the robot could clear an average of 14 objects and a maximum of 16 objects in 15 minutes. In the obstacle avoidance task, the robot succeeded five times out of six games, and in the delivery task, it succeeded four times out of six games. Throughout all the tasks, we scored 800 points twice, the highest score in the world, and won the championship. This research is aimed at the practical application of domestic service robots. We believe that the results presented in this paper demonstrate the practicality of domestic service robots in a well-developed environment. The video of the finals is available at https://youtu.be/ElUb8bfSC34?t=5511 (right side). The our source code using the simulator is available at https://github.com/Hibikino-Musashi-Home/hma_wrs_sim_ws. |
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言語 |
en |
| 書誌情報 |
en : Advanced Robotics
巻 36,
号 17-18,
p. 870-889,
発行日 2022-09-06
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| 出版社 |
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出版者 |
Taylor & Francis |
| キーワード |
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主題Scheme |
Other |
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主題 |
World Robot Challenge |
| キーワード |
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主題Scheme |
Other |
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主題 |
domestic service robot |
| キーワード |
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|
主題Scheme |
Other |
|
主題 |
pick-and-place task |
| キーワード |
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主題Scheme |
Other |
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主題 |
dataset generation |
| キーワード |
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主題Scheme |
Other |
|
主題 |
object recognition |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_6501 |
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資源タイプ |
journal article |
| 出版タイプ |
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出版タイプ |
VoR |
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出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| DOI |
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|
識別子タイプ |
DOI |
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|
関連識別子 |
https://doi.org/10.1080/01691864.2022.2115315 |
| ISSN |
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収録物識別子タイプ |
PISSN |
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収録物識別子 |
0169-1864 |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
1568-5535 |
| 研究者情報 |
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URL |
https://hyokadb02.jimu.kyutech.ac.jp/html/100000641_ja.html |
| 論文ID（連携） |
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値 |
10444462 |
| 連携ID |
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値 |
12649 |
10444462.pdf (5.2 MB)
