Estimation of ground surface radiation sources from dose map measured by moving dosimeter and 3D map

Gaku Minamoto, Eijiro Takeuchi, Satoshi Tadokoro

研究成果: Conference contribution

7 被引用数 (Scopus)

抄録

The Fukushima nuclear power plant accident that occurred in 2011 eastern Japan has created local spots with a high dose level in residential areas in eastern Japan. It is necessary to build a map of the distribution of radiation activities that shows the locations and intensities of radiation sources to assist in decontamination work. The proposed method estimates the intensities of point-like sources from the radiation dose measured by moving a dosimeter in three dimensions and 3D map of the environment, assuming that the radioactive sources are located on the ground surface. The radiation dose is measured as a few counts including a wide variability because in the proposed method, low levels of radiation are measured by moving a dosimeter. For estimating the intensities, the maximum a posteriori probability (MAP) estimation is computed on the basis of the radiation characteristics of attenuation and stochastic counts. Experiments of estimation in real environments were conducted. The experimental results showed that using the proposed method, it is possible to estimate the distributions of radiation sources using the radiation dose measured by a dosimeter and the measured 3D shape of the ground and building surface.

本文言語English
ホスト出版物のタイトルIROS 2014 Conference Digest - IEEE/RSJ International Conference on Intelligent Robots and Systems
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1889-1895
ページ数7
ISBN(電子版)9781479969340
DOI
出版ステータスPublished - 2014 1 1
イベント2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014 - Chicago, United States
継続期間: 2014 9 142014 9 18

Other

Other2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2014
CountryUnited States
CityChicago
Period14/9/1414/9/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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