Localizing multiple radiation sources actively with a particle filter
We discuss the localization of radiation sources whose number and other relevant parameters are not known in advance. The data collection is ensured by an autonomous mobile robot that performs a survey in a defined region of interest populated with static obstacles. The measurement trajectory is inf...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-02-01
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| Series: | Nuclear Engineering and Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1738573324004194 |
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| author | Tomas Lazna Ludek Zalud |
| author_facet | Tomas Lazna Ludek Zalud |
| author_sort | Tomas Lazna |
| collection | DOAJ |
| description | We discuss the localization of radiation sources whose number and other relevant parameters are not known in advance. The data collection is ensured by an autonomous mobile robot that performs a survey in a defined region of interest populated with static obstacles. The measurement trajectory is information-driven rather than pre-planned, and the localization exploits a regularized particle filter estimating the sources’ parameters continuously. Regarding the dynamic robot control, this switches between two modes, one attempting to minimize the Shannon entropy and the other aiming to reduce the variance of expected measurements in unexplored parts of the target area; both of the modes maintain safe clearance from the obstacles. The performance of the algorithms was tested in a simulation study based on real-world data acquired previously from three radiation sources exhibiting various activities. Our approach reduces the time necessary to explore the region and to find the sources by approximately 40 %; at present, however, the method is unable to reliably localize sources that have a relatively low intensity. In this context, additional research has been planned to increase the credibility and robustness of the procedure and to improve the robotic platform autonomy. |
| format | Article |
| id | doaj-art-b070be1a4fbf49d49ab5c0310291920c |
| institution | Kabale University |
| issn | 1738-5733 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Nuclear Engineering and Technology |
| spelling | doaj-art-b070be1a4fbf49d49ab5c0310291920c2025-01-31T05:10:58ZengElsevierNuclear Engineering and Technology1738-57332025-02-01572103171Localizing multiple radiation sources actively with a particle filterTomas Lazna0Ludek Zalud1Corresponding author.; Central European Institute of Technology, Brno University of Technology, Purkynova 123, Brno, 79601, Czech RepublicCentral European Institute of Technology, Brno University of Technology, Purkynova 123, Brno, 79601, Czech RepublicWe discuss the localization of radiation sources whose number and other relevant parameters are not known in advance. The data collection is ensured by an autonomous mobile robot that performs a survey in a defined region of interest populated with static obstacles. The measurement trajectory is information-driven rather than pre-planned, and the localization exploits a regularized particle filter estimating the sources’ parameters continuously. Regarding the dynamic robot control, this switches between two modes, one attempting to minimize the Shannon entropy and the other aiming to reduce the variance of expected measurements in unexplored parts of the target area; both of the modes maintain safe clearance from the obstacles. The performance of the algorithms was tested in a simulation study based on real-world data acquired previously from three radiation sources exhibiting various activities. Our approach reduces the time necessary to explore the region and to find the sources by approximately 40 %; at present, however, the method is unable to reliably localize sources that have a relatively low intensity. In this context, additional research has been planned to increase the credibility and robustness of the procedure and to improve the robotic platform autonomy.http://www.sciencedirect.com/science/article/pii/S1738573324004194Radiological source searchNuclear roboticsGamma radiationBayesian estimationSensor-based planning |
| spellingShingle | Tomas Lazna Ludek Zalud Localizing multiple radiation sources actively with a particle filter Nuclear Engineering and Technology Radiological source search Nuclear robotics Gamma radiation Bayesian estimation Sensor-based planning |
| title | Localizing multiple radiation sources actively with a particle filter |
| title_full | Localizing multiple radiation sources actively with a particle filter |
| title_fullStr | Localizing multiple radiation sources actively with a particle filter |
| title_full_unstemmed | Localizing multiple radiation sources actively with a particle filter |
| title_short | Localizing multiple radiation sources actively with a particle filter |
| title_sort | localizing multiple radiation sources actively with a particle filter |
| topic | Radiological source search Nuclear robotics Gamma radiation Bayesian estimation Sensor-based planning |
| url | http://www.sciencedirect.com/science/article/pii/S1738573324004194 |
| work_keys_str_mv | AT tomaslazna localizingmultipleradiationsourcesactivelywithaparticlefilter AT ludekzalud localizingmultipleradiationsourcesactivelywithaparticlefilter |