A fast gamma-ray source localization method for mobile robots. (October 2022)

• Record Type: Journal Article
• Authors: Tan, Wei; Zhou, Jianbin; Fang, Fang; Li, Xiaozhe; Hong, Xu
• Is Part Of: Applied radiation and isotopes. Volume 188(2022)
• Publication Date: 2022-10
• Subjects: Source localization -- Maximum likelihood estimation -- Parameter estimation -- Mobile robots; Radiology -- Periodicals; Radiation -- Industrial applications -- Periodicals; Nuclear chemistry -- Periodicals; Internet resource; Periodical; 660.298
• DOI: 10.1016/j.apradiso.2022.110377
• Languages: English
• ISSNs: 0969-8043

Abstract

Abstract: A method for fast estimation of radioactive source parameters is presented. Full use was made of multiple continuous count values, combined with triangulation with four-point sampling method to solve high-dimensional optimization to obtain initialized estimates, which converge to maximum likelihood estimation using an improved hill-climbing algorithm. Cobalt-60 search experiments were conducted in the laboratory using a mobile robot carrying a NaI(TI) detector. Experimental results showed that the method can significantly improve the computational speed. Highlights: A method for fast computing parameters of gamma-ray sources is proposed. Triangulation with four-point sampling was used to obtain initialized estimates. An improved hill-climbing algorithm is used to make the results converge to a maximum likelihood estimate. Experimental data was obtained using a robot operating system mobile robot equipped with a NaI(TI) detector.