The wing panel has numerous structural features and the distribution of scanning path points is complex, complicating scanning planning. Therefore, a line laser scanning planning method based on clustering features and path splicing is proposed. First, the features to be scanned are extracted and discretized to generate scanning viewpoints and execution path points. These viewpoints are then grouped using density-based spatial clustering of applications with noise (DBSCAN), to reduce the complexity and scale of the scanning path. Second, the improved black kite optimization algorithm (BKA) is used to plan and splice the grouped paths, to ensure scanning continuity and reduce redundant paths. Finally, an improved Hippo optimization (HO) algorithm with self-adjusting weights is used to solve the joint angles, along with a particle swarm optimization (PSO) algorithm to comprehensively optimize joint speed, acceleration, and time. The results show that the proposed method can meet the scanning planning requirements of multiple structural panel features.