自动化学报2024，Vol.50Issue(7)：1402-1416,15.DOI:10.16383/j.aas.c230297
基于多关键点检测加权融合的无人机相对位姿估计算法
Relative Pose Estimation Algorithm for Unmanned Aerial Vehicles Based on Weighted Fusion of Multiple Keypoint Detection
摘要
Abstract
A 6D target pose estimation algorithm based on multiple models keypoints weighted fusion is proposed to address the issue of low accuracy and poor robustness in obtaining the relative pose of unmanned aerial vehicles due to motion blur caused by the influence of water surface waves on the image during the landing phase of un-manned aerial vehicles.This algorithm aims to improve the accuracy and robustness of pose estimation.Firstly,based on the motion information obtained from the unmanned ship gyroscope,an inter frame jitter model is de-signed to reduce image noise by restoring image information.Then,a cascaded regression feature extraction al-gorithm with multiple models is designed to detect images obtained by the shipborne visual system through mul-tiple models,in order to enhance the diversity of the feature space;at the same time,the incremental set of keypo-int localization shapes during the detection process is used as the fusion weight to weight and fuse the model,in or-der to improve the robustness of the feature space.This paper uses efficient perspective-n-point(EPnP)to calcu-late the coordinates of the camera coordinate system for keypoints,and transforms the perspective-n-point(PnP)problem into an iterative closest point(ICP)problem.Finally,based on the dispersion of the keypoints solution set,weights are assigned to keypoints,and the ICP algorithm is used to mitigate the influence of depth information on the pose estimation.The simulation results show that this algorithm can establish a more accurate feature space,re-duce the loss of feature mapping during pose estimation,and ultimately improve the accuracy of pose estimation.关键词
辅助无人机降落/舰载视觉系统/6D位姿估计/加权融合/关键点检测/级联特征提取Key words
Assisting unmanned aerial vehicles landing/shipborne visual system/6D pose estimation/weighted fu-sion/keypoint detection/cascading feature extraction引用本文复制引用
葛泉波,李凯,张兴国..基于多关键点检测加权融合的无人机相对位姿估计算法[J].自动化学报,2024,50(7):1402-1416,15.基金项目
国家自然科学基金(62033010),江苏高校"青蓝工程"(R2023Q07)资助Supported by National Natural Science Foundation of China(62033010)and Qing Lan Project of Jiangsu Province(R2023Q07) （62033010）
