An Algorithm for Reconstructing Radiation Distribution Map in Unknown Environment Based on Mobile Robots
Abstract:Aiming at the problems of radiation distribution map reconstruction and radioactive source search and localization in unknown complex environments, a mobile robot is used to carry nuclear radiation detector and lidar for radiation data collection and regional grid map construction. The coll...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2022-12-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2154 |
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| Summary: | Abstract:Aiming at the problems of radiation distribution map reconstruction and radioactive source search and localization in unknown complex environments, a mobile robot is used to carry nuclear radiation detector and lidar for radiation data collection and regional grid map construction. The collected discrete radiation data are used to reconstruct the environmental radiation distribution map through Gaussian Process Regression (GPR). Furthermore, the radiation distribution map is fused with the regional raster map, which realizes the visualization of radiation distribution in unknown complex environment and the location of unknown radioactive source. The method can deal with complex problems such as small samples, nonlinearity and high dimension, and can quickly draw an environmental radiation distribution map. In addition, experimental verifications were carried out in real scenarios where single radioactive source was present. The experimental results show that the mobile robot can complete the reconstruction of the radiation field distribution map and estimate the location of the radioactive source in both no obstacle environment and complex obstacle environment, and the localization accuracy is higher than 0.5m. The system can be applied to search for lost radioactive source and radiation safety monitoring. |
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| ISSN: | 1007-2683 |