[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).