quaternion rotation

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Quaternion and 3D Rotation Interpolation A Mathematical Insight
Quaternions are an extension of the complex number concept, playing a crucial role in 3D space rotation. To better understand the relationship between quaternions and 3D rotations, we begin with the fundamentals of complex numbers, as there are notable parallels between the properties of complex numbers and their role in 2D rotation. Complex numbers consist of real and imaginary components, where the imaginary unit (i) is defined as ( \sqrt{-1} ), so any complex number (z) can be represented as ( z = a + bi ), with (a) as the real part and (b) as the imaginary part, where (i^2 = -1). Complex numbers can be viewed as points or vectors in the complex plane, where the real part corresponds to the x-axis and the imaginary part to the y-axis. Complex addition and subtraction are straightforward, performed by adding or subtracting the real and imaginary parts, respectively. Multiplication of complex numbers, however, is slightly more complex, requiring expansion and simplification using (i^2 = -1). A significant feature of complex multiplication is its connection to matrix multiplication. Specifically, every complex number can be associated with a particular 2x2 real matrix. For example, the complex number ( z = a + bi ) can be represented by the matrix: [ \begin{bmatrix} a & -b \\ b & a \end{bmatrix} ] This matrix form allows us to use matrix multiplication to perform complex number multiplication. During this process, we observe that complex number multiplication effectively corresponds to a rotation and scaling transformation in 2D space. For instance, the unit complex number 1 corresponds to the identity matrix, leaving points in the complex plane unchanged, while the imaginary unit (i) corresponds to a 90-degree rotation matrix, meaning that multiplying a complex number by (i) rotates it 90 degrees clockwise. After grasping these complex fundamentals, we move to quaternions. Quaternions are a further extension of complex numbers into four-dimensional space. Each quaternion consists of a real part and three imaginary parts, generally written as ( q = w + xi + yj + zk ), where (w) is the real part and (x), (y), and (z) are the imaginary parts. The units (i), (j), and (k) follow distinct multiplication rules in four-dimensional space, where quaternion multiplication is analogous to complex multiplication yet complies with four-dimensional rules. Quaternions are highly beneficial in 3D rotation operations because they avoid gimbal lock, a common issue with Euler angle representation. This makes quaternions a stable and continuous method for rotation interpolation, essential in computer graphics for 3D animation and simulation. Through quaternions, we can use linear algebra and basic geometry principles to intuitively derive and comprehend 3D spatial rotation. Quaternions provide direct representation of the rotation axis and rotation angle, while interpolating quaternions enables smooth transitions between two rotations. This is extremely helpful in animation and real-time rendering for creating fluid movement. For example, in game development and flight simulation, quaternions are often used to achieve coherent flight paths, allowing engineers to implement smooth motion.
Rotation Forest算法Juan J. Rodriguez和Ludmila I. K的集成方法
旋转森林是由Juan J. Rodriguez和Ludmila I. K在2006年提出的一种集成算法,详细介绍可见于IEEE Transactions on Pattern Analysis and Machine Intelligence的文章中(Vol.28, No. 10, PP. 1619-1630)。下载文件'RotationForest.zip'包含了根据该参考文献编写的代码,其中包括一个名为'RotationFal.m'的旋转森林算法示例子函数。
MATLAB实现矩阵乘法与四元数类(Quaternion)重点支持Modified Rodrigues参数化(MRP)
该Quaternion类(Quaternion.h)在MATLAB中实现了多种常用功能,主要包括:四元数乘积、从单位四元数转换为旋转矩阵、基本插值(SLERP)和微分运算。此类不仅支持加法、四元数乘法、标量乘法等常规操作,还特别注重Modified Rodrigues参数化(MRP),即通过MRP更新实现了旋转和四元数导数的解析计算。此外,Quaternion类通过完全模板化的精度控制,可以自动处理不同精度的四元数对象或变量进行运算。该类具备强大的功能,支持直接操作四元数,无需借助外部库,能够实现从轴角、MRP、吉布斯向量等不同参数形式的初始化,并提供必要的转换和计算操作,保证了高效与精度的平衡。