摘要
为加强转运机器人在核辐射环境下的路径规划应用,本文针对传统A^(*)算法缺乏周围环境对路径影响的问题,引入了核辐射环境下人工势场的思想对A^(*)算法评价函数进行改进,通过加入辐射源斥力函数、障碍物斥力函数以及目标点引力函数计算出栅格中受到的合力,以此让规划的路径远离周围障碍物;并对A^(*)算法的距离代价改为吸收辐射剂量代价,以及对启发式函数引入了核辐射环境下适用的动态系数,使得算法在搜索过程中有自适应权重对路径产生影响。MATLAB仿真实验表明:改进后的A^(*)算法与传统A^(*)算法相比核辐射剂量降低了52.11%~55.29%,与其他改进算法相比搜索节点数下降了34.67%~46.19%,且与辐射源和周围障碍物始终保持安全距离,具有较好的实现效果,验证了算法的有效性和优越性。
In order to enhance the path planning application of the transfer robot in a nuclear radiation environment, this paper addresses the problem of lack of influence from the surrounding environment on the path by the traditional A^(*) algorithm, and introduces the idea of an artificial potential field in the nuclear radiation environment to improve the evaluation function of this algorithm. This was achieved by obtaining the sum of the radiation source repulsion function, obstacle repulsion function, and target point gravitational force function to calculate the combined force received in the grid, thereby ensuring that the planned path is far from the surrounding environment. For the improved A^(*) algorithm, the MATLAB simulation experiments showed a decrease in the nuclear radiation dose by 52.11%~55.29% compared with the traditional A^(*) algorithm, and a decrease in the number of search nodes by 34.67%~46.19% compared with other improved algorithms. Moreover, the safety distance with the radiation sources and surrounding obstacles was constantly maintained, providing a better implementation effect and allowing the verification of the effectiveness and superiority of the improved A^(*) algorithm.
作者
邱朦文
张华
周怀芳
QIU Mengwen;ZHANG Hua;ZHOU Huaifang(Southwest University of Science&Technology,Mianyang 621010,China;Sichuan Key Laboratory of Special Enviromental Robotics,Mianyang 621010,China)
出处
《辐射研究与辐射工艺学报》
CAS
CSCD
2022年第6期51-59,共9页
Journal of Radiation Research and Radiation Processing
基金
四川省科技计划资助项目(2021YFG0376)。
关键词
转运机器人
核辐射环境
人工势场
A^(*)算法
路径规划
Transit robot
Nuclear radiation environment
Artificial potential field
A^(*)algorithm
Path planning
