Floor sensing system using laser range finder and mirror for localizing daily life commodities

Yasunobu Nohara, Tsutomu Hasegawa, Kouji Murakami

研究成果: 著書/レポートタイプへの貢献会議での発言

10 引用 (Scopus)

抄録

This paper proposes a new method of measuring position of daily commodities placed on a floor. Picking up an object on a floor will be a typical task for a robot working in our daily life environment. However, it is difficult for a robotic vision to find a small daily life object left on a large floor. The floor surface may have various texture and shadow, while other furniture may obstruct the vision. Various objects may also exist on the floor. Moreover, the surface of the object has various optical characteristics: color, metallic reflection, transparent, black etc. Our method uses a laser range finder (LRF) together with a mirror installed on the wall very close to floor. The LRF scans the laser beam horizontally just above the floor and measure the distance to the object. Some beams are reflected by the mirror and measure the distance of the object from virtually different origin. Even if the LRF fails two measurements, the method calculates the position of the object by utilizing information that the two measurements are unavailable. Thus, the method achieves two major advantages: 1) robust against occlusion and 2) applicable to variety of daily life commodities. In the experiment, success rate of observation of our method achieves 100% for any daily commodity, while that of the existing method for a cell-phone is 69.4%.

元の言語英語
ホスト出版物のタイトルIEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
ページ1030-1035
ページ数6
DOI
出版物ステータス出版済み - 12 1 2010
イベント23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Taipei, 台湾省、中華民国
継続期間: 10 18 201010 22 2010

その他

その他23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010
台湾省、中華民国
Taipei
期間10/18/1010/22/10

Fingerprint

Range finders
Mirrors
Lasers
Laser beams
Robotics
Textures
Robots
Color

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Systems Engineering

これを引用

Nohara, Y., Hasegawa, T., & Murakami, K. (2010). Floor sensing system using laser range finder and mirror for localizing daily life commodities. : IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings (pp. 1030-1035). [5649372] https://doi.org/10.1109/IROS.2010.5649372

Floor sensing system using laser range finder and mirror for localizing daily life commodities. / Nohara, Yasunobu; Hasegawa, Tsutomu; Murakami, Kouji.

IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings. 2010. p. 1030-1035 5649372.

研究成果: 著書/レポートタイプへの貢献会議での発言

Nohara, Y, Hasegawa, T & Murakami, K 2010, Floor sensing system using laser range finder and mirror for localizing daily life commodities. : IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings., 5649372, pp. 1030-1035, 23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010, Taipei, 台湾省、中華民国, 10/18/10. https://doi.org/10.1109/IROS.2010.5649372
Nohara Y, Hasegawa T, Murakami K. Floor sensing system using laser range finder and mirror for localizing daily life commodities. : IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings. 2010. p. 1030-1035. 5649372 https://doi.org/10.1109/IROS.2010.5649372
Nohara, Yasunobu ; Hasegawa, Tsutomu ; Murakami, Kouji. / Floor sensing system using laser range finder and mirror for localizing daily life commodities. IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings. 2010. pp. 1030-1035
@inproceedings{05d7955a64ad439983309c7cafaf53a6,
title = "Floor sensing system using laser range finder and mirror for localizing daily life commodities",
abstract = "This paper proposes a new method of measuring position of daily commodities placed on a floor. Picking up an object on a floor will be a typical task for a robot working in our daily life environment. However, it is difficult for a robotic vision to find a small daily life object left on a large floor. The floor surface may have various texture and shadow, while other furniture may obstruct the vision. Various objects may also exist on the floor. Moreover, the surface of the object has various optical characteristics: color, metallic reflection, transparent, black etc. Our method uses a laser range finder (LRF) together with a mirror installed on the wall very close to floor. The LRF scans the laser beam horizontally just above the floor and measure the distance to the object. Some beams are reflected by the mirror and measure the distance of the object from virtually different origin. Even if the LRF fails two measurements, the method calculates the position of the object by utilizing information that the two measurements are unavailable. Thus, the method achieves two major advantages: 1) robust against occlusion and 2) applicable to variety of daily life commodities. In the experiment, success rate of observation of our method achieves 100{\%} for any daily commodity, while that of the existing method for a cell-phone is 69.4{\%}.",
author = "Yasunobu Nohara and Tsutomu Hasegawa and Kouji Murakami",
year = "2010",
month = "12",
day = "1",
doi = "10.1109/IROS.2010.5649372",
language = "English",
isbn = "9781424466757",
pages = "1030--1035",
booktitle = "IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings",

}

TY - GEN

T1 - Floor sensing system using laser range finder and mirror for localizing daily life commodities

AU - Nohara, Yasunobu

AU - Hasegawa, Tsutomu

AU - Murakami, Kouji

PY - 2010/12/1

Y1 - 2010/12/1

N2 - This paper proposes a new method of measuring position of daily commodities placed on a floor. Picking up an object on a floor will be a typical task for a robot working in our daily life environment. However, it is difficult for a robotic vision to find a small daily life object left on a large floor. The floor surface may have various texture and shadow, while other furniture may obstruct the vision. Various objects may also exist on the floor. Moreover, the surface of the object has various optical characteristics: color, metallic reflection, transparent, black etc. Our method uses a laser range finder (LRF) together with a mirror installed on the wall very close to floor. The LRF scans the laser beam horizontally just above the floor and measure the distance to the object. Some beams are reflected by the mirror and measure the distance of the object from virtually different origin. Even if the LRF fails two measurements, the method calculates the position of the object by utilizing information that the two measurements are unavailable. Thus, the method achieves two major advantages: 1) robust against occlusion and 2) applicable to variety of daily life commodities. In the experiment, success rate of observation of our method achieves 100% for any daily commodity, while that of the existing method for a cell-phone is 69.4%.

AB - This paper proposes a new method of measuring position of daily commodities placed on a floor. Picking up an object on a floor will be a typical task for a robot working in our daily life environment. However, it is difficult for a robotic vision to find a small daily life object left on a large floor. The floor surface may have various texture and shadow, while other furniture may obstruct the vision. Various objects may also exist on the floor. Moreover, the surface of the object has various optical characteristics: color, metallic reflection, transparent, black etc. Our method uses a laser range finder (LRF) together with a mirror installed on the wall very close to floor. The LRF scans the laser beam horizontally just above the floor and measure the distance to the object. Some beams are reflected by the mirror and measure the distance of the object from virtually different origin. Even if the LRF fails two measurements, the method calculates the position of the object by utilizing information that the two measurements are unavailable. Thus, the method achieves two major advantages: 1) robust against occlusion and 2) applicable to variety of daily life commodities. In the experiment, success rate of observation of our method achieves 100% for any daily commodity, while that of the existing method for a cell-phone is 69.4%.

UR - http://www.scopus.com/inward/record.url?scp=78651519773&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78651519773&partnerID=8YFLogxK

U2 - 10.1109/IROS.2010.5649372

DO - 10.1109/IROS.2010.5649372

M3 - Conference contribution

AN - SCOPUS:78651519773

SN - 9781424466757

SP - 1030

EP - 1035

BT - IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings

ER -