基于点云位姿平均的非合作目标三维重构

3D Reconstruction of Non-Cooperative Target Using Pose Averaging on Point Clouds

针对在轨非合作目标,提出一种基于序列点云的三维重构方法,实现非合作目标交会过程中的目标三维结构恢复,并将恢复的结构用于后续点云姿态的跟踪.首先分析了非合作目标三维结构先验信息未知情况下目标相对姿态增量估计过程中的漂移问题;其次,提出一种基于位姿平均的漂移修正方法,并根据修正后的目标点云位姿对点云进行融合以实现目标的三维重构;最后,使用所提出的方法对半物理仿真试验中获取的目标点云序列进行处理,结果表明该方法能够有效地对非合作目标进行三维重构和位姿跟踪.

Considering the non-cooperative target without a prior knowledge about the 3 D structure,a consecutive point clouds based method is proposed to reconstruct the structure of non-cooperative target during the rendezvous phase.First of all,the drift problem of incremental pose estimation without a prior knowledge about 3 D structure is analyzed.Then a pose averaging based method is proposed to correct the pose drift.A structure of target is built based on the refined poses and exploited to estimate the drift-free pose of subsequent point clouds.Finally,a semi-physical experiment is carried out to verify the proposed method and the results show that the relative pose of non-cooperative target can be efficiently estimated by adopting the proposed method.