Abstract This study introduces a radiation avoidance algorithm to help radiological occupational personnel (ROP) avoid high radiation exposure in a radioactive environment. The premise of this study is that ROP can be designated as a movable point in a two-dimensional radioactive scene with known radioactive sources. A trajectory of ROP is generated by the radiation avoidance algorithm based on an artificial potential field (APF) and particle swarm optimization (PSO). In the algorithm, ROP is subjected to an attractive force from a target as well as multiple repulsive forces from multiple radioactive sources. The attractive force and repulsive forces drive ROP moving toward the target along the trajectory. APF has obvious difficulties with parameter selection and a local minima problem. So, we used the PSO algorithm to solve these difficulties of APF. Additionally, we developed a radiation avoidance simulation program using the C# programming language. Simulation experiments showed the proposed algorithm could be useful to meet the challenges of radiation avoidance applications that can be described as trajectory optimization problems.

中文翻译：

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一种基于人工势场和粒子群优化的放射性环境下避免辐射暴露的优化算法

摘要 本研究介绍了一种辐射回避算法，以帮助放射职业人员 (ROP) 避免在放射性环境中的高辐射暴露。本研究的前提是可以将ROP指定为具有已知放射源的二维放射性场景中的可移动点。ROP 的轨迹由基于人工势场 (APF) 和粒子群优化 (PSO) 的辐射回避算法生成。在该算法中，ROP 受到来自目标的吸引力以及来自多个放射源的多重排斥力。吸引力和排斥力驱动 ROP 沿轨迹向目标移动。APF 在参数选择和局部最小值问题上有明显的困难。所以，我们使用 PSO 算法来解决 APF 的这些困难。此外，我们还使用 C# 编程语言开发了防辐射模拟程序。仿真实验表明，所提出的算法可用于应对可被描述为轨迹优化问题的辐射回避应用的挑战。