基于粒子滤波和人工势场法的放射源搜寻方法

针对放射源搜寻过程中难度大、定位精度低等问题，提出了一种适用于移动机器人的自主寻源方法。该方法利用移动机器人搭载辐射探测器采集的剂量计数值，根据γ射线的衰减规律建立辐射衰减模型；在机器人前进的过程中利用粒子滤波算法对放射源的参数进行实时估计；采用高斯分布函数对重采样后的粒子进行自适应更新，保证重采样后的粒子具有多样性；根据辐射环境创建机器人路径规划模型，采用人工势场法规划机器人的自主寻源路径。实验在Matlab下进行了仿真验证，结果表明，该方法在有遮挡环境下能够搜寻到未知的单点源，同时自适应更新能够提高算法的稳定性，缩小寻源误差。

Search Method of Radioactive Source Based on Particle Filter and Artificial Potential Field

In order to solve the problems of difficulty and low positioning accuracy in the process of radioactive source search, an autonomous source finding method suitable for mobile robot is proposed. In this method, the radiation counting value collected by the mobile robot equipped with the radiation detector is used to establish the radiation attenuation model according to the attenuation law of the gamma ray, and the particle filter algorithm is used to estimate the parameters of the radiation source in real time. The Gaussian distribution function is used to adaptively update the resampled particles to ensure the diversity of the resampled particles. The robot path planning model is established according to the radiation environment, and the artificial potential field law is used to draw the automatic source-seeking path of the robot. Experiments are carried out under matlab, and the results show that the method can find unknown single point source in the occluded environment, and the adaptive updating can improve the stability of the algorithm and reduce the source search error.