移动机器人未知环境下辐射场分布地图构建算法

An Algorithm for Reconstructing Radiation Distribution Map in Unknown Environment Based on Mobile Robots

针对未知复杂环境中辐射场分布地图构建以及放射源搜寻定位等问题,利用移动机器人搭载核辐射探测器、激光雷达等进行辐射数据采集以及区域栅格地图构建;采集的离散辐射数据通过高斯过程回归方法(GPR)构建出环境辐射分布图,并将辐射分布图融合区域栅格地图,实现未知复杂环境中的辐射分布可视化及未知放射源定位。该方法能够处理小样本、非线性以及高维度等复杂问题,可快速构建环境辐射分布图。此外,在放射源存在的真实场景下开展了实验验证,实验结果表明,在无障碍物环境与复杂障碍物环境下移动机器人均能完成辐射场分布地图构建并估计出放射源所在位置,定位精度高于0.5m,可应用于搜寻丢失的放射源以及辐射安全监测。

Aiming at the problems of radiation distribution map reconstruction and radioactive source search and localization in unknown complex environments, a mobile robot is used to carry nuclear radiation detector and lidar for radiation data collection and regional grid map construction. The collected discrete radiation data are used to reconstruct the environmental radiation distribution map through Gaussian Process Regression(GPR). Furthermore, the radiation distribution map is fused with the regional raster map, which realizes the visualization of radiation distribution in unknown complex environment and the location of unknown radioactive source. The method can deal with complex problems such as small samples, nonlinearity and high dimension, and can quickly draw an environmental radiation distribution map. In addition, experimental verifications were carried out in real scenarios where single radioactive source was present. The experimental results show that the mobile robot can complete the reconstruction of the radiation field distribution map and estimate the location of the radioactive source in both no obstacle environment and complex obstacle environment, and the localization accuracy is higher than 0.5m. The system can be applied to search for lost radioactive source and radiation safety monitoring.