🤖 AI Summary
This work addresses the problem of efficiently and accurately computing the minimum distance between two ellipsoids. The authors propose an iterative algorithm based on surface sliding, which operates in the θ–φ parametric space by updating the positions of two points—one on each ellipsoid—guided by the geometric tension of the connecting line segment. The iteration proceeds until this segment becomes simultaneously normal to both ellipsoidal surfaces, ensuring convergence to the true minimal distance. The method features a clear geometric interpretation, concise analytical expressions, and low computational complexity, and it naturally extends to other smooth convex bodies. Experimental results demonstrate that the proposed approach outperforms existing methods in terms of accuracy, stability, consistency, and robustness.
📝 Abstract
We propose a novel iterative process to establish the minimum separation between two ellipsoids. The method maintains one point on each surface and updates their locations in the theta-phi parametric space. The tension along the connecting segment between the two surface points serves as the guidance for the sliding direction, and the distance between them decreases gradually. The minimum distance is established when the connecting segment becomes perpendicular to the ellipsoid surfaces, at which point the net effect of the segment tension disappears and the surface points no longer move. Demonstration examples are carefully designed, and excellent numerical performance is observed, including accuracy, consistency, stability, and robustness. Furthermore, compared to other existing techniques, this surface-sliding approach has several attractive features, such as clear geometric representation, concise formulation, a simple algorithm, and the potential to be extended straightforwardly to other situations. This method is expected to be useful for future studies in computer graphics, engineering design, material modeling, and scientific simulations.