基于改进RPN的车载导航目标识别技术  

Target recognition technology for vehicle navigation based on improved RPN

作　　者：史俊莉[1] SHI Jun-li(Henan Polytechnic Institute,Nanyang 473000,China)

机构地区：[1]河南工业职业技术学院,河南南阳473000

出　　处：《激光与红外》2022年第6期833-837,共5页Laser & Infrared

基　　金：国家自然科学青年项目(No.61803065);《控制测量技术》实践教学信息化项目(No.SXXM202004)资助。

摘　　要：车载导航是无人驾驶的一项关键技术,而其主要技术难点是动态避障,即实时目标识别与反馈控制。为了能够实时获取车辆周围目标的运动状态,提出了一种基于三维点云数据快速体素化分析的识别算法。该算法以极坐标系替代直角坐标系,直接与车载激光雷达建立映射关系。再通过区域推荐网络技术中对区域框的限定计算完成可表征目标特征的准确定位。实验采用开源数据库KITTI中的点云数据进行验证,对比了动态目标(汽车、摩托车、行人)和静态目标(树木、楼宇)之间的点云特征。识别结果与两种常用的三维目标识别算法进行对比。结果显示本算法的最优平均精度为88.45%,最优平均方向相似度为93.27%,相比常用的SECOND算法对动态目标的识别具有更好的效果。验证了其可行性,其在车载导航目标识别领域具有一定的优势。Car navigation is a key technology of unmanned driving,and its main technical difficulty is dynamic obstacle avoidance,which means real-time target recognition and feedback control.In order to obtain the real-time movement status of the targets around the vehicle,a three-dimensional point-based algorithm is proposed to replace the rectangular coordinate system with a polar coordinate system,and directly establish a mapping relationship with the vehicle-mounted lidar.Then,the accurate positioning of the characterizable target features is completed through the limited calculation of the area frame in the area recommendation network technology.The experiment is validated using point cloud data in the open source database KITTI to compare the point cloud features between dynamic targets(cars,motorcycles,pedestrians)and static targets(trees,buildings).The recognition results are compared with two commonly used 3D target recognition algorithms.The results show that the optimal average accuracy of this algorithm is 88.45%,and the optimal average direction similarity is 93.27%.The proposed algorithm has a better effect on the recognition of dynamic targets compared with the commonly used SECOND algorithm.Its feasibility is verified,and it has certain advantages in the field of vehicle navigation target recognition.

关 键 词：目标识别 点云数据 体素化 区域推荐网络 

分 类 号：TN958.98[电子电信—信号与信息处理]