Top > JRM > Identification of Unknown Multiple Radiation Sources Using Cha ...

single-rb.php

JRM Vol.37 No.5 pp. 1137-1144
doi: 10.20965/jrm.2025.p1137
(2025)

Paper:

Views over last 60 days: 23

Identification of Unknown Multiple Radiation Sources Using Change Rate of Gamma Rays with Directional Detector

Hanwool Woo ORCID Icon and Yurika Takahashi

Department of Mechanical Systems Engineering, Faculty of Engineering, Kogakuin University
2665-1 Nakano-machi, Hachioji, Tokyo 192-0015, Japan

Received:
March 6, 2025
Accepted:
May 16, 2025
Published:
October 20, 2025
Creative Commons License
Keywords:
identification of multiple radiation sources, path planning, directional gamma ray detector
Abstract

In this study, we construct a system that autonomously and efficiently generates an exploration path that enables the estimation of the distribution of multiple radiation sources, even when the source intensities are unknown. Although the gamma ray detector cannot directly measure the distance to a radiation source, we estimate this distance by analyzing the rate of change in the number of incident gamma rays and use this to localize the source. By employing this parameter, it becomes possible to accurately estimate the distance between the detector and source, thereby significantly reducing the exploration time required for localization. Additionally, we develop a method for path planning and source localization even when multiple radiation sources are distributed across an area. We verify the validity of the proposed method through simulation experiments.

Exploration for identifying radiation sources

Exploration for identifying radiation sources

Cite this article as:
H. Woo and Y. Takahashi, “Identification of Unknown Multiple Radiation Sources Using Change Rate of Gamma Rays with Directional Detector,” J. Robot. Mechatron., Vol.37 No.5, pp. 1137-1144, 2025.
Data files:
References
  1. [1] A. Ono, “Fukushima Daiichi decontamination and decommissioning: Current status and challenges,” Annals of the ICRP, Vol.50, No.1, pp. 24-30, 2021. https://doi.org/10.1177/01466453211010865
  2. [2] A. Seki, K. Saito, and H. Takemiya, “Current status of the environmental monitoring database on the accident at Fukushima Daiichi Nuclear Power Plant,” J. of Radiological Protection, Vol.41, No.3, Article No.S89, 2021. https://doi.org/10.1088/1361-6498/abfbc1
  3. [3] K. Nagatani, S. Kiribayashi, Y. Okada, K. Otake, K. Yoshida, S. Tadokoro, T. Nishimura, T. Yoshida, E. Koyanagi, M. Fukushima, and S. Kawatsuma, “Emergency response to the nuclear accident at the Fukushima Daiichi Nuclear Power Plants using mobile rescue robots,” J. of Field Robotics, Vol.30, No.1, pp. 44-63, 2013. https://doi.org/10.1002/rob.21439
  4. [4] T. Yoshida, K. Nagatani, S. Tadokoro, T. Nishimura, and E. Koyanagi, “Improvements to the Rescue Robot Quince Toward Future Indoor Surveillance Missions in the Fukushima Daiichi Nuclear Power Plant,” Proc. of the 8th Int. Conf. on Field and Service Robotics, pp. 19-32, 2014. https://doi.org/10.1007/978-3-642-40686-7_2
  5. [5] K. P. Ziock and W. H. Goldstein, “The Lost Source, Varying Backgrounds and Why Bigger May Not Be Better,” Proc. of AIP Conf., Vol.632, pp. 60-70, 2002. https://doi.org/10.1063/1.1513955
  6. [6] A. V. Klimenko, W. C. Priedhorsky, N. W. Hengartner, and K. N. Borozdin, “Efficient Strategies for Low-Statistics Nuclear Searches,” IEEE Trans. on Nuclear Science, Vol.53, No.3, pp. 1435-1442, 2006. https://doi.org/10.1109/TNS.2005.862860
  7. [7] T. Lazna and L. Zalud, “Localizing multiple radiation sources actively with a particle filter,” Nuclear Engineering and Technology, Vol.57, No.2, Article No.103171, 2025. https://doi.org/10.1016/j.net.2024.08.040
  8. [8] B. Ristic, M. Morelande, and A. Gunatilaka, “Information driven search for point sources of gamma radiation,” Signal Processing, Vol.90, No.4, pp. 1225-1239, 2010. https://doi.org/10.1016/j.sigpro.2009.10.006
  9. [9] M. Hutchinson, H. Oh, and W.-H. Chen, “Adaptive Bayesian Sensor Motion Planning for Hazardous Source Term Reconstruction,” IFAC-PapersOnLine, Vol.50, No.1, pp. 2812-2817, 2017. https://doi.org/10.1016/j.ifacol.2017.08.632
  10. [10] Z. Liu and S. Abbaszadeh, “Double Q-Learning for Radiation Source Detection,” Sensors, Vol.19, No.4, Article No.960, 2019. https://doi.org/10.3390/s19040960
  11. [11] D. Kim, H. Woo, Y. Ji, Y. Tamura, A. Yamashita, and H. Asama, “3D Radiation Imaging Using Mobile Robot Equipped with Radiation Detector,” Proc. of the 2017 IEEE/SICE Int. Symposium on System Integration, pp. 444-449, 2017. https://doi.org/10.1109/SII.2017.8279253
  12. [12] Y. Shikaze, Y. Nishizawa, Y. Sanada, T. Torii, J. Jiang, K. Shimazoe, H. Takahashi, M. Yoshino, S. Ito, T. Endo, K. Tsutsumi, S. Kato, H. Sato, Y. Usuki, S. Kurosawa, K. Kamada, and A. Yoshikawa, “Field test around Fukushima Daiichi nuclear power plant site using improved Ce:Gd3(Al,Ga)5O12 scintillator Compton camera mounted on an unmanned helicopter,” J. of Nuclear Science and Technology, Vol.53, No.12, pp. 1907-1918, 2016. https://doi.org/10.1080/00223131.2016.1185980
  13. [13] T. Kishimoto, H. Woo, R. Komatsu, Y. Tamura, H. Tomita, K. Shimazoe, A. Yamashita, and H. Asama, “Path Planning for Localization of Radiation Sources Based on Principal Component Analysis,” Applied Sciences, Vol.11, No.10, Article No.4707, 2021. https://doi.org/10.3390/app11104707
  14. [14] Y. Takahashi and H. Woo, “Path Planning for Identification of Radiation Source Using Mobile Robot with Directional Gamma-Ray Detector,” 2024 IEEE/SICE Int. Symposium on System Integration, pp. 112-116, 2024. https://doi.org/10.1109/SII58957.2024.10417702
  15. [15] H. Tomita, S. Hara, A. Mukai, K. Yamagishi, H. Ebi, K. Shimazoe, Y. Tamura, H. Woo, H. Takahashi, H. Asama, F. Ishida, E. Takada, J. Kawarabayashi, K. Tanabe, and K. Kamada, “Path-Planning System for Radioisotope Identification Devices Using 4π Gamma Imaging Based on Random Forest Analysis,” Sensors, Vol.22, No.12, Article No.4325, 2022. https://doi.org/10.3390/s22124325
  16. [16] A. Mukai, M. Kanda, K. Shimazoe, F. Ishida, E. Takada, Y. Tamura, H. Woo, H. Takahashi, M. Uenomachi, H. Asama, J. Kawarabayashi, K. Tanabe, K. Tsuchiya, K. Kamada, and H. Tomita, “Development of Unmanned Remote System to Find Radiation Sources Based on 4π Gamma Imaging,” J. Robot. Mechatron., Vol.36, No.1, pp. 79-87, 2024. https://doi.org/10.20965/jrm.2024.p0079
  17. [17] N. S. V. Rao et al., “Identification of Low-Level Point Radiation Sources Using a Sensor Network,” 2008 Int. Conf. on Information Processing in Sensor Networks, pp. 493-504, 2008. https://doi.org/10.1109/IPSN.2008.19
  18. [18] J. M. Hite, J. K. Mattingly, K. L. Schmidt, R. Ştefanescu, and R. Smith, “Bayesian metropolis methods applied to sensor networks for radiation source localization,” 2016 IEEE Int. Conf. on Multisensor Fusion and Integration for Intelligent Systems (MFI), pp. 389-393, 2016. https://doi.org/10.1109/MFI.2016.7849519
  19. [19] K. D. Jarman, E. A. Miller, R. S. Wittman, and C. J. Gesh, “Bayesian Radiation Source Localization,” Nuclear Technology, Vol.175, No.1, pp. 326-334, 2011. https://doi.org/10.13182/NT10-72
  20. [20] P. M. Djuric et al., “Particle filtering,” IEEE Signal Processing Magazine, Vol.20, No.5, pp. 19-38, 2003. https://doi.org/10.1109/MSP.2003.1236770

Creative Commons License  This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 19, 2025