Rotations and poses are ubiquitous throughout many fields of science and engineering such as robotics, aerospace, computer vision and graphics. In this paper, we provide a complete characterization of rotations and poses in terms of the eigenstructure of their matrix Lie group representations, SO(3), SE(3) and Ad(SE(3)). An eigendecomposition of the pose representations reveals that they can be cast into a form very similar to that of rotations although the structure of the former can vary depending on the relative nature of the translation and rotation involved. Understanding the eigenstructure of these important quantities has merit in and of itself but it is also essential to appreciating such practical results as the minimal polynomial for rotations and poses and the calculation of Jacobians; moreover, we can speak of a principal-axis pose in much the same manner that we can of a principal-axis rotation.
翻译:在许多科学和工程领域,如机器人、航空航天、计算机视觉和图形,都普遍存在轮廓和姿势,本文对轮廓作了完整描述,并按矩阵结构构成Lie小组代表、SO(3)、SE(3)和Ad(SE(3))等矩阵结构,对摆势表示的细微分解表明,可以采取与轮廓形式非常相似的形式,尽管前者的结构可能因所涉翻译和轮换的相对性质而不同。了解这些重要数量的机率结构本身是有道理的,但同样重要的是,必须赞赏各种实际结果,如关于轮换、姿势和计算雅各布人的最低多指数;此外,我们可以说,主要轴构成的方式与我们能够进行主轴旋转的方式大致相同。