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A radioactive source searching algorithm based on Gaussian Process Regression

  • Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Robots have been applied to search for radioactive sources. Until now, however, it is still an open problem to accomplish this task by one autonomous robot. In this paper, we propose an algorithm based on Gaussian Process Regression (GPR) to search for a radioactive source in a discrete 2D environment. We predict the radiation intensities of 8 positions using GPR. We consider searching a radioactive source as an optimization problem so as to obtain target positions for a mobile robot. The objective function describes three aspects: the radiation intensity, the amount of information for GPR, and the environment with obstacles. Simulation experiments are conducted to verify the proposed algorithm. The simulation results show that our algorithm is effective and robust when searching radioactive sources located at different points in an indoor environment.

Original languageEnglish
Title of host publication2015 IFToMM World Congress Proceedings, IFToMM 2015
PublisherNational Taiwan University
ISBN (Electronic)9789860460988
DOIs
StatePublished - 2015
Event14th International Federation for the Promotion of Mechanism and Machine Science World Congress, IFToMM 2015 - Taipei, Taiwan, Province of China
Duration: 25 Oct 201530 Oct 2015

Publication series

Name2015 IFToMM World Congress Proceedings, IFToMM 2015

Conference

Conference14th International Federation for the Promotion of Mechanism and Machine Science World Congress, IFToMM 2015
Country/TerritoryTaiwan, Province of China
CityTaipei
Period25/10/1530/10/15

Keywords

  • Autonomous robot
  • Gaussian Process Regression
  • Radioactive sources
  • Searching algorithm

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