著者

栗田 雄一 祖父江 厚志 池田 篤俊 小笠原 司

出版者

一般社団法人 日本ロボット学会

雑誌

日本ロボット学会誌 (ISSN:02891824)

巻号頁・発行日

vol.29, no.4, pp.361-368, 2011 (Released:2011-06-15)

参考文献数

20

被引用文献数

1

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In this paper, we present a water volume estimation method in various cups using the glass harp acoustics. When a rigid probe flicks a glass, sounds arise. Since the sounds alter depending on the water volume in the glass, we can utilize the sound information to estimate the water volume. In order to model the acoustics characteristics of various glasses, we propose the relational expression between the water volume and the vibration frequency that improves Oku's expression. By using the proposed relational expressions and a flicking motion by a robotic finger with a microphone, we confirm the proposed method can estimate the water volume with the accuracy of 1–3%.

著者

吉本 公則 佐藤 諒 石原 佑彌 山口 明彦 吉川 雅博 池田 篤俊 高松 淳 小笠原 司

出版者

一般社団法人 日本機械学会

雑誌

ロボティクス・メカトロニクス講演会講演概要集 2014 (ISSN:24243124)

巻号頁・発行日

pp._3P1-S03_1-_3P1-S03_4, 2014-05-24 (Released:2017-06-19)

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It is important to realize the robot handling soft objects. In this paper, we treat a string as an example of soft objects. Humans can create various figures with a string; we aim to develop a robot system that can do such a thing. We employ the string figures as the task. We propose a framework with which a robot can play string figures with a human. Concretely, we develop a description method that can represent a variety of procedures of string figures to be played by a robot and a human pair. In order to implement this framework on a dual-arm robot, we also develop a method to decide centers of loops to be picked up using camera images. This paper demonstrates the experimental results with a dual-arm robot Hiro-NX.

著者

鈴木 直弥 上田 陽平 高垣 直尚 植木 巌 池田 篤俊

出版者

Advanced Marine Science and Technology Society

雑誌

海洋理工学会誌 (ISSN:13412752)

巻号頁・発行日

vol.27, no.1, pp.73-79, 2022-07-30 (Released:2022-08-27)

参考文献数

23

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Drag coefficient on the ocean surface is determined by various studies based on different mechanisms, such as turbulence and wave breaking, closely related to wind speed. The global ocean datasets of wind speed are distributed by various temporal resolutions based on reanalysis, assimilation, and satellite data. Recently, the wind speed data with higher temporal resolution have been provided. Using 6-hourly and hourly wind datasets, the air-sea momentum fluxes were estimated by several drag coefficient models proposed by Large & Yeager (2009), Andreas et al. (2012), Takagaki et al. (2012), & Hwang (2018). The globally averaged annual mean air-sea momentum fluxes were derived from the different drag coefficient models. The maximum difference of the annual mean values among the models reaches approximately 30% of annual mean values. The meridional structure of zonally averaged annual mean air-sea momentum flux has double peak at relatively higher latitudes from 40°S/N to 60°N/S. At those peaks maximum difference among the models reaches more than 30% of the zonally averaged annual mean. In terms of differences in temporal resolution on the wind speed datasets on each grid, the differences between hourly and 6-hourly wind data became larger with decreasing average period. The maximum difference of 66.7% was recognized on daily mean. The large difference was remarkable in higher wind speed regions, such as typhoon’s paths in the western Pacific. The effects of wind variability on different temporal resolution datasets are significant for estimating the air-sea momentum flux.

著者

池田 篤俊

出版者

奈良先端科学技術大学院大学

巻号頁・発行日

2010

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博士論文

著者

平田 鷹志 山崎 亘 カヤオ クリスチャンデウス 吉川 雅博 池田 篤俊 高松 淳 小笠原 司

出版者

一般社団法人 日本機械学会

雑誌

ロボティクス・メカトロニクス講演会講演概要集 2015 (ISSN:24243124)

巻号頁・発行日

pp._2P1-E03_1-_2P1-E03_3, 2015-05-17 (Released:2017-06-19)

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Recently, cleaning robots are becoming widely used. However, even if commercially-available cleaning robots can collect dust and small debris on the floor, they can not pick up trash such as PET bottles, cans, etc. We developed a cleaning robot intended for picking trash while dust collecting. This paper describes the architecture of the cleaning robot consisting of hardware such as an RGB-D sensor, a robot arm and a commercially-available cleaning robot, and also software for trash picking such as searching trash from RGB-D image, picking the trash via the robot arm and controlling the cleaning robot. We used commercially-available hardware and open source software such as Robot Operating System (ROS), Point Cloud Libraly (PCL) and so on.