#include <iostream>
//using namespace std;
#include <Eigen/Core>
#include <Eigen/Dense>
#include <Eigen/Geometry>
#include <Eigen/LU>
#include <Eigen/SVD>
using namespace Eigen;
using namespace std;
int main()
{
Eigen::Quaterniond q1;
Eigen::Quaterniond q2;
q1.w() = 0.96103;
q1.x() = -0.02726;
q1.y() = -0.01015;
q1.z() = -0.27489;
q2.w() = 0.68673;
q2.x() = -0.67238;
q2.y() = -0.21366;
q2.z() = -0.17510;
Eigen::Quaterniond q = q1 * q2;
cout << q.w() << endl;
cout << q.x() << endl;
cout << q.y() << endl;
cout << q.z() << endl;
// inverse 求出 q2
q = q.inverse() * q1;
cout << "\n\n";
cout << q.w() << endl;
cout << q.x() << endl;
cout << q.y() << endl;
cout << q.z() << endl;
/*
* Determine the inverse of q = [1 0 1 0]:
* qinv = quatinv([1 0 1 0])
* qinv = 0.5000 0 -0.5000 0
*/
Eigen::Quaterniond q3;
q3.w() = 1;
q3.x() = 0;
q3.y() = 1;
q3.z() = 0;
q3 = q3.inverse();
cout << q3.w() << endl;
cout << q3.x() << endl;
cout << q3.y() << endl;
cout << q3.z() << endl;
return 0;
}
##Eigen::Vector3d()
Eigen::Vector3d pos;
pos << 0.0,-2.0,1.0;
Eigen::Vector3d pos2 = Eigen::Vector3d(1,-3,0.5);
pos = pos+pos2;
Eigen::Vector3d pos3 = Eigen::Vector3d::Zero();
pos.normalize();
pos.inverse();
//Dot and Cross Product
Eigen::Vector3d v(1, 2, 3);
Eigen::Vector3d w(0, 1, 2);
double vDotw = v.dot(w); // dot product of two vectors
Eigen::Vector3d vCrossw = v.cross(w); // cross product of two vectors
##Eigen::Quaterniond()
Eigen::Quaterniond rot;
Eigen::Vector3d pos;
pos << 0.0,-2.0,1.0;
rot.setFromTwoVectors(Eigen::Vector3d(0,1,0), pos);
Eigen::Matrix<double,3,3> rotationMatrix;
rotationMatrix = rot.toRotationMatrix();
Eigen::Quaterniond q(2, 0, 1, -3);
std::cout << "This quaternion consists of a scalar " << q.w()
<< " and a vector " << std::endl << q.vec() << std::endl;
q.normalize();
std::cout << "To represent rotation, we need to normalize it such
that its length is " << q.norm() << std::endl;
Eigen::Vector3d vec(1, 2, -1);
Eigen::Quaterniond p;
p.w() = 0;
p.vec() = vec;
Eigen::Quaterniond rotatedP = q * p * q.inverse();
Eigen::Vector3d rotatedV = rotatedP.vec();
std::cout << "We can now use it to rotate a vector " << std::endl
<< vec << " to " << std::endl << rotatedV << std::endl;
// convert a quaternion to a 3x3 rotation matrix:
Eigen::Matrix3d R = q.toRotationMatrix();
std::cout << "Compare with the result using an rotation matrix "
<< std::endl << R * vec << std::endl;
Eigen::Quaterniond a = Eigen::Quaterniond::Identity();
Eigen::Quaterniond b = Eigen::Quaterniond::Identity();
Eigen::Quaterniond c;
// Adding two quaternion as two 4x1 vectors is not supported by the Eigen API.
//That is, c = a + b is not allowed. The solution is to add each element:
c.w() = a.w() + b.w();
c.x() = a.x() + b.x();
c.y() = a.y() + b.y();
c.z() = a.z() + b.z();
##Eigen::Affine3d()
Affine3d is a Pose type message( contains a Vector 3d and Quaterniond/RotationMatrix). It is great for computing several subsequent transformations.
Eigen::Affine3d aff = Eigen::Affine3d::Identity();
aff.translation() = pos;
aff.translation() = Eigen::Vector3d(0.7,0.4,1.1);
aff.linear() = rot.toRotationMatrix();
aff.translate(Eigen::Vector3d(0,0.0,0.03));
aff.pretranslate(pos);
aff.rotate(Eigen::AngleAxisd(M_PI, Eigen::Vector3d(0,0,1)));
aff.prerotate(rot.toRotationMatrix());
Eigen::MatrixXd normalMatrix = aff.linear().inverse().transpose();
To get the translation and rotation portions:
pos = aff.translation();
rot = aff.linear();
aff.linear().col(0);
##Eigen::MatrixXd()
//Transpose and inverse:
Eigen::MatrixXd A(3, 2);
A << 1, 2,
2, 3,
3, 4;
Eigen::MatrixXd B = A.transpose();// the transpose of A is a 2x3 matrix
// computer the inverse of BA, which is a 2x2 matrix:
Eigen::MatrixXd C = (B * A).inverse();
C.determinant(); //compute determinant
Eigen::Matrix3d D = Eigen::Matrix3d::Identity();
Eigen::Matrix3d m = Eigen::Matrix3d::Random();
m = (m + Eigen::Matrix3d::Constant(1.2)) * 50;
Eigen::Vector3d v2(1,2,3);
cout << "m =" << endl << m << endl;
cout << "m * v2 =" << endl << m * v2 << endl;
//Accessing matrices:
Eigen::MatrixXd A2 = Eigen::MatrixXd::Random(7, 9);
std::cout << "The fourth row and 7th column element is " << A2(3, 6) << std::endl;
Eigen::MatrixXd B2 = A2.block(1, 2, 3, 3);
std::cout << "Take sub-matrix whose upper left corner is A(1, 2)"
<< std::endl << B2 << std::endl;
Eigen::VectorXd a2 = A2.col(1); // take the second column of A
Eigen::VectorXd b2 = B2.row(0); // take the first row of B2
Eigen::VectorXd c2 = a2.head(3);// take the first three elements of a2
Eigen::VectorXd d2 = b2.tail(2);// take the last two elements of b2
#include <iostream>
//using namespace std;
#include <Eigen/Core>
#include <Eigen/Dense>
#include <Eigen/Geometry>
#include <Eigen/LU>
#include <Eigen/SVD>
using namespace Eigen;
using namespace std;
int main()
{
Eigen::Quaterniond rot;
Eigen::Vector3d pos;
pos << 0.0,-2.0,1.0;
rot.setFromTwoVectors(Eigen::Vector3d(0, 1, 0), pos);
Eigen::Matrix<double, 3, 3> rotationMatrix;
rotationMatrix = rot.toRotationMatrix();
Eigen::Quaterniond q(2, 0, 1, -3);
std::cout << "This quaternion consists of a scalar " << q.w()
<< " and a vector " << std::endl << q.vec() << std::endl;
q.normalize();
std::cout << "To represent rotation, we need to normalize it such that its length is " << q.norm() << std::endl;
Eigen::Vector3d vec(1, 2, -1);
Eigen::Quaterniond p;
p.w() = 0;
p.vec() = vec;
Eigen::Quaterniond rotatedP = q * p * q.inverse();
Eigen::Vector3d rotatedV = rotatedP.vec();
std::cout << "We can now use it to rotate a vector " << std::endl
<< vec << " to " << std::endl << rotatedV << std::endl;
// convert a quaternion to a 3x3 rotation matrix:
Eigen::Matrix3d R = q.toRotationMatrix();
std::cout << "Compare with the result using an rotation matrix " << std::endl << R* vec << std::endl;
Eigen::Quaterniond a = Eigen::Quaterniond::Identity();
Eigen::Quaterniond b = Eigen::Quaterniond::Identity();
Eigen::Quaterniond c;
// Adding two quaternion as two 4x1 vectors is not supported by the Eigen API.
//That is, c = a + b is not allowed. The solution is to add each element:
c.w() = a.w() + b.w();
c.x() = a.x() + b.x();
c.y() = a.y() + b.y();
c.z() = a.z() + b.z();
}
#include <iostream>
//using namespace std;
#include <Eigen/Core>
#include <Eigen/Dense>
#include <Eigen/Geometry>
#include <Eigen/LU>
#include <Eigen/SVD>
using namespace Eigen;
using namespace std;
int main()
{
// Eigen/Geometry 模塊提供了各種旋轉和平移的表示
// 3D 旋轉矩陣直接使用 Matrix3d 或 Matrix3f
Eigen::Matrix3d rotation_matrix = Eigen::Matrix3d::Identity();
// 旋轉向量使用 AngleAxis, 它底層不直接是Matrix,但運算可以當作矩陣(因為重載了運算符)
Eigen::AngleAxisd rotation_vector(M_PI / 4, Eigen::Vector3d(0, 0,
1)); //沿 Z 軸旋轉 45 度
cout .precision(3);
cout << "rotation matrix =\n" << rotation_vector.matrix() <<
endl; //用matrix()轉換成矩陣
// 也可以直接賦值
rotation_matrix = rotation_vector.toRotationMatrix();
// 用 AngleAxis 可以進行座標變換
Eigen::Vector3d v(1, 0, 0);
Eigen::Vector3d v_rotated = rotation_vector * v;
cout << "(1,0,0) after rotation = " << v_rotated.transpose() << endl;
// 或者用旋轉矩陣
v_rotated = rotation_matrix * v;
cout << "(1,0,0) after rotation = " << v_rotated.transpose() << endl;
// 歐拉角: 可以將旋轉矩陣直接轉換成歐拉角
Eigen::Vector3d euler_angles = rotation_matrix.eulerAngles(2, 1,
0); // ZYX順序,即roll pitch yaw順序
cout << "yaw pitch roll = " << euler_angles.transpose() << endl;
// 歐氏變換矩陣使用 Eigen::Isometry
Eigen::Isometry3d T =
Eigen::Isometry3d::Identity(); // 雖然稱為3d,實質上是4*4的矩陣
T.rotate(rotation_vector); // 按照rotation_vector進行旋轉
T.pretranslate(Eigen::Vector3d(1, 3, 4)); // 把平移向量設成(1,3,4)
cout << "Transform matrix = \n" << T.matrix() << endl;
// 用變換矩陣進行座標變換
Eigen::Vector3d v_transformed = T * v; // 相當於R*v+t
cout << "v tranformed = " << v_transformed.transpose() << endl;
// 對於仿射和射影變換,使用 Eigen::Affine3d 和 Eigen::Projective3d 即可,略
// 四元數
// 可以直接把AngleAxis賦值給四元數,反之亦然
Eigen::Quaterniond q = Eigen::Quaterniond(rotation_vector);
cout << "quaternion = \n" << q.coeffs() <<
endl; // 請注意coeffs的順序是(x,y,z,w),w為實部,前三者為虛部
// 也可以把旋轉矩陣賦給它
q = Eigen::Quaterniond(rotation_matrix);
cout << "quaternion = \n" << q.coeffs() << endl;
// 使用四元數旋轉一個向量,使用重載的乘法即可
v_rotated = q * v; // 注意數學上是qvq^{-1}
cout << "(1,0,0) after rotation = " << v_rotated.transpose() << endl;
}