Yu Zihan, Ge Qiaode Jeffrey, Langer Mark P, Arbab Mona
Computational Design Kinematics Lab, Stony Brook University-SUNY, Stony Brook, NY 11794, USA.
Radiation Oncology Department, Indiana University, Indianapolis, IN 46202, USA.
Adv Mech Mach Sci (2023). 2023;147:777-785. doi: 10.1007/978-3-031-45705-0_75. Epub 2023 Nov 5.
This paper deals with the problem of estimating confidence regions of a set of uncertain spatial displacements for a given level of confidence or probabilities. While a direct application of the commonly used statistic methods to the coordinates of the moving frame is straight-forward, it is also the least effective in that it grossly overestimate the confidence region. Based on the dual-quaternion representation, this paper introduces the notion of the kinematic confidence ellipsoids as an alternative to the existing method called rotation and translation confidence limit (RTCL). An example is provided to demonstrate how the kinematic confidence ellipsoids can be computed.
本文探讨了在给定置信水平或概率下,估计一组不确定空间位移的置信区域的问题。虽然将常用统计方法直接应用于移动框架的坐标很简单,但也是最无效的,因为它会严重高估置信区域。基于对偶四元数表示,本文引入了运动学置信椭球体的概念,作为一种替代现有方法——旋转和平移置信极限(RTCL)的方法。文中给出了一个例子来说明如何计算运动学置信椭球体。