摘要
随着核技术的广泛应用,利用移动机器人代替人工进入未知辐射环境执行核应急任务愈发重要。然而,机器人受限于探测时间与传感器性能,仅能获取稀疏的辐射数据,但为了便于开展核安全监测工作,必须获取环境中的辐射场分布和放射源的位置。针对上述问题,提出一种融合二维激光SLAM与辐射特征的源项定位方法。该方法利用移动机器人搭载核辐射探测器、激光雷达等传感器进行辐射数据采集和环境地图构建;然后,基于高斯过程回归方法反演出区域辐射场,并将反演的辐射场融合到SLAM环境地图中;最后使用霍夫变换方法定位未知放射源。此外,在放射源存在的真实环境下开展了实验验证,实验结果表明:在采用Gmapping、Hector和Cartographer三种激光SLAM算法构建占用栅格地图的基础上,空地和厂房两种环境中均能够完成全局辐射环境地图的融合,且定位精度高于0.29 m。
With the widespread application of nuclear technology,the use of mobile robots to replace human operators in executing nuclear emergency tasks within unknown radiation environments has become increasingly important.However,due to limitations in detection time and sensor performance,robots can only obtain sparse radiation data.Nonetheless,in order to facilitate nuclear safety monitoring,it is essential to obtain the radiation fields distribution and the locations of radioactive sources in the environment.To address the above problems,a source localization method integrating two-dimensional laser SLAM and radiation features is proposed.This method uses mobile robots equipped with nuclear radiation detectors,LiDAR,and other sensors to collect radiation data and construct environmental maps.Subsequently,it uses Gaussian process regression method to invert the regional radiation field and integrates the inverted radiation field into the SLAM environmental map.Finally,the Hough transform method is applied to locate unknown radioactive sources.In addition,experimental verification is conducted in real environments where radioactive sources are present.The experimental results show that based on occupancy grid maps constructed using three laser SLAM algorithms(Gmapping,Hector,and Cartographer),the fusion of global radiation environment maps can be completed in both open space and factory environments,with localization accuracy exceeding 0.29 m.
作者
霍建文
周中兵
郭云磊
周怀芳
HUO Jianwen;ZHOU Zhongbing;GUO Yunlei;ZHOU Huaifang(School of Information Control Engineering,Southwest University of Science and Technology,Mianyang 621010)
出处
《导航与控制》
2025年第6期103-113,共11页
Navigation and Control
基金
国家自然科学基金(编号:12205245,12175187)
四川省自然科学基金(编号:2025NSFSC1946)。
关键词
辐射环境
移动机器人
SLAM
辐射地图构建
放射源定位
radiation environment
mobile robots
SLAM
radiation map construction
radiation source localization
