The paper introduces the FFD (Free Form Deformation) method based on the elastomeric theory into the aircraft aerodynamic configuration design, which provides a quick and efficient way to parameterization geometry and generate the calculation grids automatically. With analysis of the theory, it concludes characteristics of FFD. According to use the FFD method to the parameterization and the grid generation, airfoil optimization design system based on genetic algorithm and wing cowling optimization design system based on genetic algorithm and Kriging surrogate model are established in this paper, respectively. The optimization design for drag reduction on airfoil based on NACA0012 and the wing-cowling based on wing body of DLRF4 are used to give examples there. The results of the optimization design are remarkable, which obviously proves the FFD method is useful in the aerodynamic optimization design.

Object-level SLAM is a new development direction in SLAM technology. To better understand the scene, it not only focuses on building an environmental map and robot localization but also emphasizes identifying, tracking, and constructing specific objects in the environment. To address the issues of localization and pose estimation caused by spatial geometric feature distortion of objects in complex application scenarios, we propose a distributed joint pose estimation optimization method. This method, based on globally dense fused features, provides accurate global feature representation and employs an iterative optimization algorithm within the algorithm framework for pose refinement. Simultaneously, it completes visual localization and object state optimization through a joint factor graph algorithm. Finally, by employing parallel processing, it achieves precise optimization of localization and object pose, effectively solving the optimization error drift problem and realizing accurate visual localization and object pose estimation.