At present, aircraft radome coating cleaning mainly relies on manual and chemical methods. In view of this situation, this study presents a trajectory planning method based on a three-dimensional (3D) surface point cloud for a laser-enabled coating cleaning robot. An automated trajectory planning scheme is proposed to utilize 3D laser scanning to acquire point cloud data and avoid the dependence on traditional teaching–playback paradigms. A principal component analysis (PCA) algorithm incorporating additional principal direction determination for point cloud alignment is introduced to facilitate subsequent point cloud segmentation. The algorithm can adjust the coordinate system and align with the desired point cloud segmentation direction efficiently and conveniently. After preprocessing and coordinate system adjustment of the point cloud, a projection-based point cloud segmentation technique is proposed, enabling the slicing division of the point cloud model and extraction of cleaning target positions from each slice. Subsequently, the normal vectors of the cleaning positions are estimated, and trajectory points are biased along these vectors to determine the end effector’s orientation. Finally, B-spline curve fitting and layered smooth connection methods are employed to generate the cleaning path. Experimental results demonstrate that the proposed method offers efficient and precise trajectory planning for the aircraft radar radome coating laser cleaning and avoids the need for a prior teaching process so it could enhance the automation level in coating cleaning tasks.

This study investigates the mechanical behavior and failure mechanisms of SFHCPs under low-velocity impact and compression after impact (CAI) conditions. Symmetric foam-filled hat-stiffened composite panels (SFHCPs) are widely used in critical load-bearing structures such as vessels and aircraft due to their high strength-to-weight ratio and integrated stiffener design. However, due to the material’s high sensitivity to impact, it is necessary to conduct a systematic evaluation of its application reliability. By integrating experimental testing and numerical simulation, the buckling modes characterized by symmetry and envelope number were adopted as key performance indicators. The integration of an optical buckling measurement method with iterative finite element model (FEM) updates significantly enhances model accuracy and computational efficiency. Experimental results indicate that for specimens impacted at the mid-section of the stiffener the residual compressive strength drops sharply from 106 kN to 40.6 kN (a reduction of 61.7%), with the buckling mode changing from a symmetric four-wave pattern in the undamaged state to localized buckling in the impact region, leading to brittle failure. The integration of FPP data improved the accuracy of the FEM, highlighting the critical influence of the symmetry of the buckling mode in optimizing impact-resistant composite structures.