Journal of Radiation Research and Radiation Processing, Volume. 42, Issue 1, 010601(2024)

Complete coverage path planning of nuclear radiation field using bio-inspired neural network

Zhaojin LUO1, Chengfeng LIU1, Wenbao JIA1,2, Qing SHAN1, Chao SHI1, Jiandong ZHANG1, Daqian HEI3, Xiaojun ZHANG4, and Yongsheng LING1,2、*
Author Affiliations
  • 1Institute of Nuclear Analysis Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • 2Jiangsu University Collaborative Innovation Center for Radiation Medicine, Suzhou 215031, China
  • 3College of Nuclear Science and Technology, Lanzhou University, Nanjing 211106, China
  • 4Suzhou Guanrui Information Technology Co., Ltd., Suzhou 215008, China
  • show less
    References(20)

    [1] Liliang LIU. Play a role of nuclear power base support Attention to nuclear safety. China Securities Jour-nal.

    [2] Zhenggang ZHANG. Research on path planning of inspection robot in nuclear environment(2022).

    [3] Yicheng SUN. Research on path planning of intelligent mowing robot based on A* and DWA fusion algorithm(2022).

    [4] Long CHENG, Xin WANG, Di WU et al. Scrubbing path planning of bathing robot based on improved artificial potential field method. Application Research of Computers, 40, 2760-2764(2023).

    [5] Sheng QU. Research on path planning of unmanned ship b ased on improved rapid expansion random tree method(2023).

    [6] Longlong TAO, Pengcheng LONG, Xiaolei ZHENG et al. An improved A* algorithm-guided path-planning method for radioactive environment. Journal of Radiation Research and Radiation Processing, 36, 060601(2018).

    [7] Qi YUE. Research on the inversion method of multiple nuclide source terms in nuclear accidents based on machine learning(2021).

    [8] Mengwen QIU, Hua ZHANG, Huaifang ZHOU. Path planning for nuclear radiation environments based on an improved artificial potential field A* algorithm. Journal of Radiation Research and Radiation Processing, 40, 060601(2022).

    [9] Jingyu WU, Shiqiang ZHU, Wei SONG et al. Coverage path planning based on improved cellular decomposition. Systems Engineering and Electronics, 1-12(2023).

    [10] Wei SONG, Jingyu WU, Tao ZHENG et al. A full-coverage path planning method and device combining cattle farming mo-tion with genetic algorithm.

    [11] Fangfang ZHANG, Bo CHEN, Xuanxuan BAN et al. Multi-robot cooperative search algorithm based on bio-inspired neural network and DMPC. Control and Decision, 36, 2699-2706(2021).

    [12] Jianye MA, Dongjian ZHENG, Jianwei SUN. Path planning algorithm for underwater dam surface apparent cracks detection based on bio-inspired neural network. Advances in Science and Technology of Water Resources, 42, 60-65(2022).

    [13] Jianwen HUO, Yunlei GUO, Li HU et al. Radioactive source search method based on improved particle filter and bioinspired neural network.

    [14] Daqi ZHU, Yu LIU, Bing SUN et al. Autonomous underwater vehicles path planning based on autonomous inspired Glasius bio-inspired neural network algorithm. Control Theory & Applications, 36, 183-191(2019).

    [15] Lili FAN, Qizhi WANG, Fuchun SUN. Simulation research and improvement on biologically inspired neural network path planning. Journal of Beijing Jiaotong University (Natural Edition), 30, 84-88(2006).

    [16] Shen LI. A full coverage path planning algorithm based on new element decomposition method. The Journal of New Industrialization, 11, 58-60(2021).

    [17] M A V J Muthugala, S M B P Samarakoon, M R Elara. Toward energy-efficient online complete coverage path planning of a ship hull maintenance robot based on glasius bio-inspired neural network. Expert Systems With Applications, 187, 115940(2022).

    [18] Min PENG, Zehong DU, Wei DONG et al. Multi-machine area coverage algorithm based on improved Niu Geng method and inertial trajectory. Mechatronics, 28, 19-25(2022).

    [19] Huinan ZHAO, Shuhua LIU, Fuzhang WU et al. Research on boustrothedon complete coverage path planning based on binary search. Computer Engineering and Applications, 47, 51-53(2011).

    [20] Aolin SUN, Xiang CAO, Xu XIAO et al. Multi-AUV target searching based on the biologically inspired neural network. Ship Electronic Engineering, 39, 32-36(2019).

    Tools

    Get Citation

    Copy Citation Text

    Zhaojin LUO, Chengfeng LIU, Wenbao JIA, Qing SHAN, Chao SHI, Jiandong ZHANG, Daqian HEI, Xiaojun ZHANG, Yongsheng LING. Complete coverage path planning of nuclear radiation field using bio-inspired neural network[J]. Journal of Radiation Research and Radiation Processing, 2024, 42(1): 010601

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Research Articles

    Received: Oct. 20, 2023

    Accepted: Nov. 23, 2023

    Published Online: Mar. 27, 2024

    The Author Email: LING Yongsheng (凌永生)

    DOI:10.11889/j.1000-3436.2023-0093

    Topics