A modified A* algorithm for path planning in the radioactive environment of nuclear facilities

被引:0
|
作者
Zhang, Biao [1 ]
Cai, Xingfu [1 ]
Li, Guoqiang [2 ]
Li, Xiaomeng [3 ]
Peng, Minjun [4 ]
Yang, Miao [1 ]
机构
[1] Xian Res Inst High Tech, Xian 710025, Peoples R China
[2] China Inst Radiat Protect, Taiyuan 030006, Peoples R China
[3] China Nucl Power Engn Co Ltd, HeBei Branch, Shijiazhuang 050000, Peoples R China
[4] Harbin Engn Univ, Harbin 150001, Peoples R China
关键词
Modified A* algorithm; Heuristic search; Path planning; Radioactive environment;
D O I
10.1016/j.anucene.2025.111233
中图分类号
TL [原子能技术]; O571 [原子核物理学];
学科分类号
0827 ; 082701 ;
摘要
The search efficiency is low when using the traditional A* algorithm for radiation field path planning. In order to prevent the situation where one of the two cost functions of F(n) in the A* algorithm is significantly larger than the other, this paper presents a predicted cost method as a heuristic function of the A* algorithm and creates a weighting scheme to balance the actual and predicted costs in the A* algorithm. The results of path planning show that the modified A* algorithm has a search direction, which increases algorithm efficiency while guaranteeing low dose. The total cumulative dose of the route of the modified A* algorithm is better than that of the traditional A* algorithm and probabilistic road map method(PRM). The calculation results of the two models show that the modified A* algorithm is slightly lower than the traditional A* algorithm in terms of cumulative dose, which is reduced by 5.35% compared with the PRM algorithm. In terms of the number of algorithm execution points, the modified A* algorithm is 57.18% lower than the traditional A* algorithm on average. In terms of calculation time, the modified A* algorithm is 13.79% shorter than the traditional A* algorithm. The PRM algorithm has the shortest time, but the results of the PRM algorithm are random and unstable. The modified A* algorithm has the search direction under the premise of keeping the low dose, which improves the efficiency of the algorithm. Therefore, the modified A* algorithm can be used as an effective reference for staff path planning.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] A modified ant optimization algorithm for path planning of UCAV
    Chen Mou
    Wu Qing-xian
    Jiang Chang-sheng
    APPLIED SOFT COMPUTING, 2008, 8 (04) : 1712 - 1718
  • [22] Path planning of robot using modified dijkstra Algorithm
    Fusic, S. Julius
    Ramkumar, P.
    Hariharan, K.
    2018 NATIONAL POWER ENGINEERING CONFERENCE (NPEC), 2018,
  • [23] Path planning with modified A star algorithm for a mobile robot
    Duchon, Frantisek
    Babinec, Andrej
    Kajan, Martin
    Beno, Peter
    Florek, Martin
    Fico, Tomas
    Jurisica, Ladislav
    MODELLING OF MECHANICAL AND MECHATRONIC SYSTEMS, 2014, 96 : 59 - 69
  • [24] Global Path Planning Using Modified Firefly Algorithm
    Chen, Xiaochao
    Zhou, Ming
    Huang, Jian
    Luo, Zhiwei
    2017 INTERNATIONAL SYMPOSIUM ON MICRO-NANOMECHATRONICS AND HUMAN SCIENCE (MHS), 2017,
  • [25] Path Planning of UCAV Based on a Modified GeesePSO Algorithm
    Fu, Zheng-Fang
    INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, ICIC 2012, 2012, 7390 : 471 - 478
  • [26] Hybrid IACO-A*-PSO optimization algorithm for solving multiobjective path planning problem of mobile robot in radioactive environment
    Zhang, De
    Yin, Ye-bo
    Luo, Run
    Zou, Shu-liang
    PROGRESS IN NUCLEAR ENERGY, 2023, 159
  • [27] The multi-objective inspection path-planning in radioactive environment based on an improved ant colony optimization algorithm
    Xie, Xingwen
    Tang, Zhihong
    Cai, Jiejin
    PROGRESS IN NUCLEAR ENERGY, 2022, 144
  • [28] The multi-objective inspection path-planning in radioactive environment based on an improved ant colony optimization algorithm
    Xie, Xingwen
    Tang, Zhihong
    Cai, Jiejin
    PROGRESS IN NUCLEAR ENERGY, 2022, 144
  • [29] The path-planning in radioactive environment based on HIOSD-PRM method
    Xiao, Q.
    Cai, J.
    ANNALS OF NUCLEAR ENERGY, 2022, 171
  • [30] Study on the Illite Modification for Removal of Radioactive Cesium in Water Environment near Nuclear Facilities
    Hwang, Jeonghwan
    Choung, Sungwook
    Shin, Woosik
    Han, Weon Shik
    ECONOMIC AND ENVIRONMENTAL GEOLOGY, 2018, 51 (02): : 113 - 120