Purpose

This paper aims to propose a fast and robust 3D point set registration method for pose estimation of assembly features with few distinctive local features in the manufacturing process.

Design/methodology/approach

The distance between the two 3D objects is analytically approximated by the implicit representation of the target model. Specifically, the implicit B-spline surface is adopted as an interface to derive the distance metric. With the distance metric, the point set registration problem is formulated into an unconstrained nonlinear least-squares optimization problem. Simulated annealing nested Gauss-Newton method is designed to solve the non-convex problem. This integration of gradient-based optimization and heuristic searching strategy guarantees both global robustness and sufficient efficiency.

Findings

The proposed method improves the registration efficiency while maintaining high accuracy compared with several commonly used approaches. Convergence can be guaranteed even with critical initial poses or in partial overlapping conditions. The multiple flanges pose estimation experiment validates the effectiveness of the proposed method in real-world applications.

Originality/value

The proposed registration method is much more efficient because no feature estimation or point-wise correspondences update are performed. At each iteration of the Gauss–Newton optimization, the poses are updated in a singularity-free format without taking the derivatives of a bunch of scalar trigonometric functions. The advantage of the simulated annealing searching strategy is combined to improve global robustness. The implementation is relatively straightforward, which can be easily integrated to realize automatic pose estimation to guide the assembly process.

中文翻译：

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使用模拟退火嵌套高斯牛顿优化的装配特征位姿估计的点集配准

目的

本文旨在提出一种快速且鲁棒的 3D 点集配准方法，用于装配特征的姿态估计，在制造过程中几乎没有明显的局部特征。

设计/方法/方法

两个 3D 对象之间的距离通过目标模型的隐式表示在解析上近似。具体而言，采用隐式 B 样条曲面作为接口来导出距离度量。使用距离度量，点集配准问题被公式化为无约束非线性最小二乘优化问题。模拟退火嵌套高斯-牛顿法是为了解决非凸问题而设计的。这种基于梯度的优化和启发式搜索策略的集成保证了全局鲁棒性和足够的效率。

发现

与几种常用方法相比，所提出的方法提高了配准效率，同时保持了高精度。即使在临界初始姿势或部分重叠条件下也可以保证收敛。多法兰姿态估计实验验证了该方法在实际应用中的有效性。

原创性/价值

所提出的配准方法效率更高，因为没有执行特征估计或逐点对应更新。在 Gauss-Newton 优化的每次迭代中，位姿都以无奇点的格式更新，而无需采用一堆标量三角函数的导数。结合模拟退火搜索策略的优点，提高全局鲁棒性。实现比较简单，可以很容易地集成到实现自动位姿估计来指导装配过程。