基于C-TOF成像的位姿测量与地物目标识别技术研究  

Research on pose measurement and ground object recognition technology based on C-TOF imaging

作　　者：卢纯青[1] 杨孟飞[2] 武延鹏[1] 梁潇[1] Lu Chunqing;Yang Mengfei;Wu Yanpeng;Liang Xiao(Beijing Institute of Control Engineering,Beijing 100080,China;China Academy of Space Technology,Beijing 100094,China)

机构地区：[1]北京控制工程研究所,北京100080 [2]中国空间技术研究院,北京100094

出　　处：《红外与激光工程》2020年第1期213-221,共9页Infrared and Laser Engineering

基　　金：十三五预研基金。

摘　　要：深空探测器的功耗和体积有限,任务工况多样,与低轨道地球探测器相比,深空探测器对导航敏感器的任务能力提出了更高的需求。提出了一种基于飞行时间成像的快速位姿测量和地物目标识别技术。为了在保证位姿测量精度的前提下满足对位姿测量时间性能的需求,提出了一种基于深度信息的动态尺度估计方法。该方法提升了物方多尺度变化条件下点云配准的时间稳定性,平均配准时间缩短60%以上,平均配准精度约为0.04 m。为了满足多尺度、多形态地物目标识别的需求,使用了基于轻量化深度神经网络,可根据场景深度信息进行地物检测。结果表明,该方法可对地物特征进行快速感知,在真实场景中的准确率达到70%以上。Deep space probes have limited power consumption and volume,and have diverse mission conditions.Compared with low-orbit earth probes,deep space probes have higher requirements for the mission capabilities of navigation sensors.This paper proposed a fast pose measurement and ground object recognition technology based on time-of-flight imaging.In order to meet the time requirements of pose measurement under the premise of ensuring the accuracy of pose measurement,a dynamic scale estimation method based on depth information was proposed.This method improved the temporal stability of point cloud registration under multi-scale object-side changes.The average registration time was reduced by more than 60%and the average registration accuracy was about 0.04 m.In order to meet the needs of multi-scale and multi-morph object recognition,a light-weight deep neural network was used to detect ground objects based on scene depth information.The results show that this method can quickly perceive the features of ground features,and the accuracy rate is more than 70%in real scenes.

关 键 词：深空探测 飞行时间成像 正态分布变换 语义分割 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]