size_t closest_point_index_rayOMP(const pcl::PointCloud<PointT>& cloud,
const Eigen::Vector3f& direction_pre,
const Eigen::Vector3f& line_pt,
double& distance_to_ray) {
Eigen::Vector3f direction = direction_pre / direction_pre.norm();
PointT point;
std::vector<double> distances(cloud.points.size(), 10); // Initialize to value 10
// Generate a vector of distances
#pragma omp parallel for
for (size_t index = 0; index < cloud.points.size(); index++) {
point = cloud.points[index];
Eigen::Vector3f cloud_pt(point.x, point.y, point.z);
Eigen::Vector3f difference = (line_pt - cloud_pt);
// https://en.wikipedia.org/wiki/Distance_from_a_point_to_a_line#Vector_formulation
double distance = (difference - (difference.dot(direction) * direction)).norm();
distances[index] = distance;
}
double min_distance = std::numeric_limits<double>::infinity();
size_t min_index = 0;
// Find index of maximum (TODO: Figure out how to OMP this)
for (size_t index = 0; index < cloud.points.size(); index++) {
const double distance = distances[index];
if (distance < min_distance) {
min_distance = distance;
min_index = index;
}
}
distance_to_ray = min_distance;
return (min_index);
}
bool CommandSubscriber::getForcedTfFrame(Eigen::Affine3f & result) const
{
tf::StampedTransform transform;
try
{
m_tf_listener.lookupTransform(m_forced_tf_frame_reference,m_forced_tf_frame_name,ros::Time(0),transform);
}
catch (tf::TransformException ex)
{
ROS_ERROR("kinfu: hint was forced by TF, but retrieval failed because: %s",ex.what());
return false;
}
Eigen::Vector3f vec;
vec.x() = transform.getOrigin().x();
vec.y() = transform.getOrigin().y();
vec.z() = transform.getOrigin().z();
Eigen::Quaternionf quat;
quat.x() = transform.getRotation().x();
quat.y() = transform.getRotation().y();
quat.z() = transform.getRotation().z();
quat.w() = transform.getRotation().w();
result.linear() = Eigen::AngleAxisf(quat).matrix();
result.translation() = vec;
return true;
}
void NodeRendererEvent::render( const Eigen::Matrix4f& view, const Eigen::Matrix4f& model )
{
glPushMatrix();
glMultMatrixf( ( model * view ).array() );
glColor3f( 1.0f, 1.0f, 0.0f );
// render a filled elipse
glBegin( GL_POLYGON );
for ( float step = 0.0f; step < 2.0f * M_PI; step += 0.1f )
{
float x = GEOM_WIDTH * sinf( step );
float y = GEOM_HEIGHT * cosf( step );
glVertex3f( x, y, 0.0f );
}
glEnd();
// render the border
if ( _isHighlighted )
{
Eigen::Vector3f col = RenderManager::get()->getHeighlightColour();
glColor3f( col.x(), col.y(), col.z() );
}
else
{
glColor3f( 0.3f, 0.3f, 0.0f );
}
glLineWidth( 8.0f );
glBegin( GL_LINE_LOOP );
for ( float step = 0.0f; step < 2.0f * M_PI; step += 0.05f )
{
float x = ( GEOM_WIDTH + 0.9f ) * sinf( step );
float y = ( GEOM_HEIGHT + 0.9f ) * cosf( step );
glVertex3f( x, y, 0.0f );
}
glEnd();
// render the node text
glColor3f( 0.0, 0.0, 0.0 );
std::string text( getText() );
if ( text.length() )
{
Eigen::Vector3f tmin, tmax;
RenderManager::get()->fontGetDims( text.c_str(), tmin, tmax );
float xpos = tmax.x() - tmin.x();
float ypos = tmax.y() - tmin.y();
if ( getScale().x() )
xpos /= getScale().x();
if ( getScale().y() )
ypos /= getScale().y();
Eigen::Vector2f pos( -xpos / 2.0f, -ypos / 2.0f );
RenderManager::get()->fontRender( text.c_str(), pos );
}
glPopMatrix();
}
void EXPORT_API InitShapeMatching(float* restPositions, float* invMasses, bool* posLocks, int pointsCount, float* restCMs, float* invRestMat)
{
Eigen::Vector3f* X_0 = new Eigen::Vector3f[pointsCount];
float* w = new float[pointsCount];
for (size_t i = 0; i < pointsCount; i++)
{
X_0[i] = Eigen::Map<Eigen::Vector3f>(restPositions + (i * 4));
w[i] = posLocks[i] ? 0.0f : invMasses[i];
}
Eigen::Vector3f restCM;
Eigen::Matrix3f A;
PBD::PositionBasedDynamics::initShapeMatchingRestInfo(X_0, w, pointsCount, restCM, A);
restCMs[0] = restCM.x();
restCMs[1] = restCM.y();
restCMs[2] = restCM.z();
restCMs[3] = 0.0f;
invRestMat[0] = A(0, 0); invRestMat[1] = A(0, 1); invRestMat[2] = A(0, 2);
invRestMat[4] = A(1, 0); invRestMat[5] = A(1, 1); invRestMat[6] = A(1, 2);
invRestMat[8] = A(2, 0); invRestMat[9] = A(2, 1); invRestMat[10]= A(2, 2);
delete[] X_0;
delete[] w;
}
void EXPORT_API InitTetrasShapeMatchingJB(btVector3* initialPositions,float* invMasses, bool* posLocks, Tetrahedron* tetras, btVector3* restCMs, float* invRestMat, int tetrasCount)
{
for (int i = 0; i < tetrasCount; i++)
{
Tetrahedron tetra = tetras[i];
Eigen::Vector3f x1_0(initialPositions[tetra.idA].x(), initialPositions[tetra.idA].y(), initialPositions[tetra.idA].z());
Eigen::Vector3f x2_0(initialPositions[tetra.idB].x(), initialPositions[tetra.idB].y(), initialPositions[tetra.idB].z());
Eigen::Vector3f x3_0(initialPositions[tetra.idC].x(), initialPositions[tetra.idC].y(), initialPositions[tetra.idC].z());
Eigen::Vector3f x4_0(initialPositions[tetra.idD].x(), initialPositions[tetra.idD].y(), initialPositions[tetra.idD].z());
float w1 = posLocks[tetra.idA] ? 0.0f : invMasses[tetra.idA];
float w2 = posLocks[tetra.idB] ? 0.0f : invMasses[tetra.idB];
float w3 = posLocks[tetra.idC] ? 0.0f : invMasses[tetra.idC];
float w4 = posLocks[tetra.idD] ? 0.0f : invMasses[tetra.idD];
Eigen::Vector3f restCM;
Eigen::Matrix3f A;
Eigen::Vector3f x0[4] = { x1_0, x2_0, x3_0, x4_0 };
float w[4] = { w1, w2, w3, w4 };
Eigen::Vector3f corr[4];
PBD::PositionBasedDynamics::initShapeMatchingRestInfo(x0, w, 4, restCM, A);
restCMs[i] = btVector3(restCM.x(), restCM.y(), restCM.z());
invRestMat[16 * i + 0] = A(0, 0); invRestMat[16 * i + 1] = A(0, 1); invRestMat[16 * i + 2] = A(0, 2);
invRestMat[16 * i + 4] = A(1, 0); invRestMat[16 * i + 5] = A(1, 1); invRestMat[16 * i + 6] = A(1, 2);
invRestMat[16 * i + 8] = A(2, 0); invRestMat[16 * i + 9] = A(2, 1); invRestMat[16 * i +10] = A(2, 2);
}
}
/**
* Verifica si un plano corta a una nube en dos
* @param pc nube de puntos a evaluar
* @param coefs Coeficientes del plano
* @return True si lo corta, false en caso contrario.
*/
bool isPointCloudCutByPlane(PointCloud<PointXYZ>::Ptr pc, ModelCoefficients::Ptr coefs, PointXYZ p_plane){
/*
Algoritmo:
- Obtener vector normal a partir de coeficientes
- Iterar sobre puntos de la nube
- Calcular vector delta entre punto entregado (dentro del plano) y punto iterado
- Calcular ángulo entre vector delta y normal
- Angulos menores a PI/2 son de un lado, mayores son de otro
- Si aparecen puntos de ambos lados, retornar True, else, false.
*/
const double PI = 3.1416;
Eigen::Vector3f normal = Eigen::Vector3f(coefs->values[0], coefs->values[1], coefs->values[2]);
normal.normalize();
// cout << "Normal: " << normal << endl;
bool side;
// Iterar sobre los puntos
for (int i=0; i<pc->points.size(); i++){
// Calcular ángulo entre punto y normal
Eigen::Vector3f delta = Eigen::Vector3f (p_plane.x, p_plane.y, p_plane.z) - Eigen::Vector3f(pc->points[i].x, pc->points[i].y, pc->points[i].z);
delta.normalize();
double alpha = acos(normal.dot(delta));
// printf ("Alpha: %f°\n", (alpha*180/PI));
if (i==0){
side = (alpha < PI/2.0);
// printf("Lado escogido: %s", side ? "true": "false");
continue;
}
if (side != (alpha < PI/2.0)){
// printf("Nube es cortada por plano\n");
return true;
}
}
// printf("Nube NO es cortada por plano\n");
return false;
}
void WorldDownloadManager::findExtraCubesForBoundingBox(const Eigen::Vector3f& current_cube_min,
const Eigen::Vector3f& current_cube_max,const Eigen::Vector3f& bbox_min,const Eigen::Vector3f& bbox_max,Vector3fVector& cubes_centers,
bool& extract_current)
{
const Eigen::Vector3f & cube_size = current_cube_max - current_cube_min;
cubes_centers.clear();
extract_current = false;
const Eigen::Vector3f relative_act_bbox_min = bbox_min - current_cube_min;
const Eigen::Vector3f relative_act_bbox_max = bbox_max - current_cube_min;
const Eigen::Vector3i num_cubes_plus = Eigen::Vector3f(floor3f(Eigen::Vector3f(relative_act_bbox_max.array() / cube_size.array())
- (Eigen::Vector3f::Ones() * 0.0001))).cast<int>();
const Eigen::Vector3i num_cubes_minus = Eigen::Vector3f(floor3f(Eigen::Vector3f(relative_act_bbox_min.array() / cube_size.array())
+ (Eigen::Vector3f::Ones() * 0.0001))).cast<int>();
for (int z = num_cubes_minus.z(); z <= num_cubes_plus.z(); z++)
for (int y = num_cubes_minus.y(); y <= num_cubes_plus.y(); y++)
for (int x = num_cubes_minus.x(); x <= num_cubes_plus.x(); x++)
{
const Eigen::Vector3i cube_index(x,y,z);
if ((cube_index.array() == Eigen::Vector3i::Zero().array()).all())
{
extract_current = true;
continue;
}
const Eigen::Vector3f relative_cube_origin = cube_index.cast<float>().array() * cube_size.array();
const Eigen::Vector3f cube_center = relative_cube_origin + current_cube_min + (cube_size * 0.5);
cubes_centers.push_back(cube_center);
}
}
void SensorFusion::reset(const Eigen::Vector3f& accel, const Eigen::Vector3f& magnetom)
{
G_Dt = 0;
Eigen::Vector3f temp1;
Eigen::Vector3f temp2;
Eigen::Vector3f xAxis;
xAxis << 1.0f, 0.0f, 0.0f;
timestamp = highResClock.now();
// GET PITCH
// Using y-z-plane-component/x-component of gravity vector
pitch = -atan2f(accel(0), sqrtf(accel(1) * accel(1) + accel(2) * accel(2)));
// GET ROLL
// Compensate pitch of gravity vector
temp1 = accel.cross(xAxis);
temp2 = xAxis.cross(temp1);
// Normally using x-z-plane-component/y-component of compensated gravity vector
// roll = atan2(temp2[1], sqrt(temp2[0] * temp2[0] + temp2[2] * temp2[2]));
// Since we compensated for pitch, x-z-plane-component equals z-component:
roll = atan2f(temp2(1), temp2(2));
// GET YAW
compassHeading(magnetom);
yaw = magHeading;
// Init rotation matrix
init_rotation_matrix(dcmMatrix, yaw, pitch, roll);
}
void adjustNormalsToViewPoints(
const pcl::PointCloud<pcl::PointXYZ>::Ptr & viewpoints,
pcl::PointCloud<pcl::PointXYZRGBNormal> & cloud)
{
if(viewpoints->size() && cloud.size())
{
pcl::search::KdTree<pcl::PointXYZ>::Ptr tree (new pcl::search::KdTree<pcl::PointXYZ>);
tree->setInputCloud (viewpoints);
for(unsigned int i=0; i<cloud.size(); ++i)
{
std::vector<int> indices;
std::vector<float> dist;
tree->nearestKSearch(pcl::PointXYZ(cloud.points[i].x, cloud.points[i].y, cloud.points[i].z), 1, indices, dist);
UASSERT(indices.size() == 1);
Eigen::Vector3f v = viewpoints->at(indices[0]).getVector3fMap() - cloud.points[i].getVector3fMap();
Eigen::Vector3f n(cloud.points[i].normal_x, cloud.points[i].normal_y, cloud.points[i].normal_z);
float result = v.dot(n);
if(result < 0)
{
//reverse normal
cloud.points[i].normal_x *= -1.0f;
cloud.points[i].normal_y *= -1.0f;
cloud.points[i].normal_z *= -1.0f;
}
}
}
}
float robotDepth()
{
// Two interesting points
float alpha1 = (x + (sx-height)/2)/(float)height*2*tan(VFOV/2.);
float alpha2 = (x - (sx+height)/2)/(float)height*2*tan(VFOV/2.);
float beta = (y - width/2)/(float)width*2*tan(HFOV/2.);
// Vectors
Eigen::Vector3f v1(1,-beta,-alpha1);
Eigen::Vector3f v2(1,-beta,-alpha2);
// Normalization
v1 = v1/v1.norm();
v2 = v2/v2.norm();
// Center
Eigen::Vector3f c = (v1+v2)/2.;
float c_norm = c.norm();
// Projection
Eigen::MatrixXf proj_mat = c.transpose()*v1;
float proj = proj_mat(0,0);
// Orthogonal part in v1
Eigen::Vector3f orth = v1 - proj/c_norm*c;
// Norm
float orth_norm = orth.norm();
// Approximate depth
float d = H/2.*proj/orth_norm;
return d;
}
png::image<png::rgb_pixel_16> bumpier::model::calculate_normals(const png::image<png::gray_pixel_16>& input, double phi, space_type space) const
{
int width = input.get_width(), height = input.get_height();
png::image<png::rgb_pixel_16> output(width, height);
for (int y = 0; y < height; y++)
for (int x = 0; x < width; x++)
{
int xmin = (x + width - 1) % width,
ymin = (y + height - 1) % height,
xmax = (x + 1) % width,
ymax = (y + 1) % height;
Eigen::Vector3f normal = (position(input, x, ymax) - position(input, x, ymin)).cross(
position(input, xmax, y) - position(input, xmin, y));
if(space == tangent_space)
normal = tangentspace(Eigen::Vector2f((float)x / width, (float)y / height)) * normal;
normal.normalize();
normal = (normal.array() * 0.5 + 0.5) * 0xFFFF;
output.set_pixel(x, y, png::rgb_pixel_16(normal[0], normal[1], normal[2]));
}
return output;
}
void m2tq(Eigen::Vector3f& t, Eigen::Quaternionf& q, const Eigen::Matrix4f& m){
t.x()=m(0,3);
t.y()=m(1,3);
t.z()=m(2,3);
Eigen::Matrix3f R=m.block<3,3>(0,0);
q=Eigen::Quaternionf(R);
}
template <typename PointNT> bool
pcl::GridProjection<PointNT>::isIntersected (const std::vector<Eigen::Vector4f, Eigen::aligned_allocator<Eigen::Vector4f> > &end_pts,
std::vector<Eigen::Vector3f, Eigen::aligned_allocator<Eigen::Vector3f> > &vect_at_end_pts,
std::vector <int> &pt_union_indices)
{
assert (end_pts.size () == 2);
assert (vect_at_end_pts.size () == 2);
double length[2];
for (size_t i = 0; i < 2; ++i)
{
length[i] = vect_at_end_pts[i].norm ();
vect_at_end_pts[i].normalize ();
}
double dot_prod = vect_at_end_pts[0].dot (vect_at_end_pts[1]);
if (dot_prod < 0)
{
double ratio = length[0] / (length[0] + length[1]);
Eigen::Vector4f start_pt = end_pts[0] + (end_pts[1] - end_pts[0]) * ratio;
Eigen::Vector4f intersection_pt = Eigen::Vector4f::Zero ();
findIntersection (0, end_pts, vect_at_end_pts, start_pt, pt_union_indices, intersection_pt);
Eigen::Vector3f vec;
getVectorAtPoint (intersection_pt, pt_union_indices, vec);
vec.normalize ();
double d2 = getD2AtPoint (intersection_pt, vec, pt_union_indices);
if (d2 < 0)
return (true);
}
return (false);
}
template <typename PointNT> void
pcl::GridProjection<PointNT>::getProjectionWithPlaneFit (const Eigen::Vector4f &p,
std::vector<int> (&pt_union_indices),
Eigen::Vector4f &projection)
{
// Compute the plane coefficients
Eigen::Vector4f model_coefficients;
/// @remark iterative weighted least squares or sac might give better results
Eigen::Matrix3f covariance_matrix;
Eigen::Vector4f xyz_centroid;
computeMeanAndCovarianceMatrix (*data_, pt_union_indices, covariance_matrix, xyz_centroid);
// Get the plane normal
EIGEN_ALIGN16 Eigen::Vector3f::Scalar eigen_value = -1;
EIGEN_ALIGN16 Eigen::Vector3f eigen_vector;
pcl::eigen33 (covariance_matrix, eigen_value, eigen_vector);
// The normalization is not necessary, since the eigenvectors from libeigen are already normalized
model_coefficients[0] = eigen_vector [0];
model_coefficients[1] = eigen_vector [1];
model_coefficients[2] = eigen_vector [2];
model_coefficients[3] = 0;
// Hessian form (D = nc . p_plane (centroid here) + p)
model_coefficients[3] = -1 * model_coefficients.dot (xyz_centroid);
// Projected point
Eigen::Vector3f point (p.x (), p.y (), p.z ()); //= Eigen::Vector3f::MapAligned (&output.points[cp].x, 3);
float distance = point.dot (model_coefficients.head <3> ()) + model_coefficients[3];
point -= distance * model_coefficients.head < 3 > ();
projection = Eigen::Vector4f (point[0], point[1], point[2], 0);
}
template <typename PointSource, typename PointTarget, typename NormalT, typename Scalar> int
pcl::registration::FPCSInitialAlignment <PointSource, PointTarget, NormalT, Scalar>::selectBaseTriangle (std::vector <int> &base_indices)
{
int nr_points = static_cast <int> (target_indices_->size ());
float best_t = 0.f;
// choose random first point
base_indices[0] = (*target_indices_)[rand () % nr_points];
int *index1 = &base_indices[0];
// random search for 2 other points (as far away as overlap allows)
for (int i = 0; i < ransac_iterations_; i++)
{
int *index2 = &(*target_indices_)[rand () % nr_points];
int *index3 = &(*target_indices_)[rand () % nr_points];
Eigen::Vector3f u = target_->points[*index2].getVector3fMap () - target_->points[*index1].getVector3fMap ();
Eigen::Vector3f v = target_->points[*index3].getVector3fMap () - target_->points[*index1].getVector3fMap ();
float t = u.cross (v).squaredNorm (); // triangle area (0.5 * sqrt(t)) should be maximal
// check for most suitable point triple
if (t > best_t && u.squaredNorm () < max_base_diameter_sqr_ && v.squaredNorm () < max_base_diameter_sqr_)
{
best_t = t;
base_indices[1] = *index2;
base_indices[2] = *index3;
}
}
// return if a triplet could be selected
return (best_t == 0.f ? -1 : 0);
}
boost::optional<Intersection> Triangle::intersect(Ray ray) {
Eigen::Vector3f s1 = ray.dir.cross(d2);
const float div = s1.dot(d1);
if(div <= 0) { // parallel or back
return boost::optional<Intersection>();
}
const float div_inv = 1 / div;
Eigen::Vector3f s = ray.org - p0;
const float a = s.dot(s1) * div_inv;
if(a < 0 || a > 1) {
return boost::optional<Intersection>();
}
Eigen::Vector3f s2 = s.cross(d1);
const float b = ray.dir.dot(s2) * div_inv;
if(b < 0 || a + b > 1) {
return boost::optional<Intersection>();
}
const float t = d2.dot(s2) * div_inv;
if(t < 0) {
return boost::optional<Intersection>();
}
return boost::optional<Intersection>(Intersection(
t,
ray.at(t),
normal,
(1 - a - b) * uv0 + a * uv1 + b * uv2,
(1 - a - b) * ir0 + a * ir1 + b * ir2,
attribute));
}
// This algorithm comes from Sebastian O.H. Madgwick's 2010 paper:
// "An efficient orientation filter for inertial and inertial/magnetic sensor arrays"
// https://www.samba.org/tridge/UAV/madgwick_internal_report.pdf
static void _psmove_orientation_fusion_imu_update(
PSMoveOrientation *orientation_state,
float delta_t,
const Eigen::Vector3f ¤t_omega,
const Eigen::Vector3f ¤t_g)
{
// Current orientation from earth frame to sensor frame
Eigen::Quaternionf SEq = orientation_state->quaternion;
Eigen::Quaternionf SEq_new = SEq;
// Compute the quaternion derivative measured by gyroscopes
// Eqn 12) q_dot = 0.5*q*omega
Eigen::Quaternionf omega = Eigen::Quaternionf(0.f, current_omega.x(), current_omega.y(), current_omega.z());
Eigen::Quaternionf SEqDot_omega = Eigen::Quaternionf(SEq.coeffs() * 0.5f) *omega;
if (current_g.isApprox(Eigen::Vector3f::Zero(), k_normal_epsilon))
{
// Get the direction of the gravitational fields in the identity pose
PSMove_3AxisVector identity_g= psmove_orientation_get_gravity_calibration_direction(orientation_state);
Eigen::Vector3f k_identity_g_direction = Eigen::Vector3f(identity_g.x, identity_g.y, identity_g.z);
// Eqn 15) Applied to the gravity vector
// Fill in the 3x1 objective function matrix f(SEq, Sa) =|f_g|
Eigen::Matrix<float, 3, 1> f_g;
psmove_alignment_compute_objective_vector(SEq, k_identity_g_direction, current_g, f_g, NULL);
// Eqn 21) Applied to the gravity vector
// Fill in the 4x3 objective function Jacobian matrix: J_gb(SEq)= [J_g]
Eigen::Matrix<float, 4, 3> J_g;
psmove_alignment_compute_objective_jacobian(SEq, k_identity_g_direction, J_g);
// Eqn 34) gradient_F= J_g(SEq)*f(SEq, Sa)
// Compute the gradient of the objective function
Eigen::Matrix<float, 4, 1> gradient_f = J_g * f_g;
Eigen::Quaternionf SEqHatDot =
Eigen::Quaternionf(gradient_f(0, 0), gradient_f(1, 0), gradient_f(2, 0), gradient_f(3, 0));
// normalize the gradient
psmove_quaternion_normalize_with_default(SEqHatDot, *k_psmove_quaternion_zero);
// Compute the estimated quaternion rate of change
// Eqn 43) SEq_est = SEqDot_omega - beta*SEqHatDot
Eigen::Quaternionf SEqDot_est = Eigen::Quaternionf(SEqDot_omega.coeffs() - SEqHatDot.coeffs()*beta);
// Compute then integrate the estimated quaternion rate
// Eqn 42) SEq_new = SEq + SEqDot_est*delta_t
SEq_new = Eigen::Quaternionf(SEq.coeffs() + SEqDot_est.coeffs()*delta_t);
}
else
{
SEq_new = Eigen::Quaternionf(SEq.coeffs() + SEqDot_omega.coeffs()*delta_t);
}
// Make sure the net quaternion is a pure rotation quaternion
SEq_new.normalize();
// Save the new quaternion back into the orientation state
orientation_state->quaternion = SEq_new;
}
void
pd_solver_advance(struct PdSolver *solver, uint32_t const n_iterations)
{
/* set external force */
Eigen::VectorXf ext_accel = Eigen::VectorXf::Zero(solver->positions.size());
#pragma omp parallel for
for (uint32_t i = 0; i < solver->positions.size()/3; ++i)
for (int j = 0; j < 3; ++j)
ext_accel[3*i + j] = solver->ext_force[j];
Eigen::VectorXf const ext_force = solver->mass_mat*ext_accel;
Eigen::VectorXf const mass_y = solver->mass_mat*(2.0f*solver->positions - solver->positions_last);
solver->positions_last = solver->positions;
for (uint32_t iter = 0; iter < n_iterations; ++iter) {
/* LOCAL STEP */
/* LOCAL STEP (we account everything except the global solve */
struct timespec local_start;
clock_gettime(CLOCK_MONOTONIC, &local_start);
uint32_t const n_constraints = solver->n_attachments + solver->n_springs;
Eigen::VectorXf d(3*n_constraints);
for (uint32_t i = 0; i < solver->n_attachments; ++i) {
struct PdConstraintAttachment c = solver->attachments[i];
d.block<3, 1>(3*i, 0) = Eigen::Map<Eigen::Vector3f>(c.position);
}
uint32_t const offset = solver->n_attachments;
for (uint32_t i = 0; i < solver->n_springs; ++i) {
struct PdConstraintSpring c = solver->springs[i];
Eigen::Vector3f const v = solver->positions.block<3, 1>(3*c.i[1], 0)
- solver->positions.block<3, 1>(3*c.i[0], 0);
d.block<3, 1>(3*(offset + i), 0) = v.normalized()*c.rest_length;
}
Eigen::VectorXf const b = mass_y + solver->t2*(solver->j_mat*d + ext_force);
struct timespec local_end;
clock_gettime(CLOCK_MONOTONIC, &local_end);
/* GLOBAL STEP */
struct timespec global_start;
clock_gettime(CLOCK_MONOTONIC, &global_start);
solve(solver, b);
struct timespec global_end;
clock_gettime(CLOCK_MONOTONIC, &global_end);
solver->global_time = pd_time_diff_ms(&global_start, &global_end);
solver->local_time = pd_time_diff_ms(&local_start, &local_end);
solver->global_cma = (solver->global_time + solver->n_iters*solver->global_cma)/(solver->n_iters + 1);
solver->local_cma = (solver->local_time + solver->n_iters*solver->local_cma)/(solver->n_iters + 1);
if (!(solver->n_iters % 1000)) {
printf("Local CMA: %f ms\n", solver->local_cma);
printf("Global CMA: %f ms\n\n", solver->global_cma);
}
++solver->n_iters;
}
}
template<typename PointT, typename LeafT, typename BranchT, typename OctreeT> int
pcl::octree::OctreePointCloud<PointT, LeafT, BranchT, OctreeT>::getApproxIntersectedVoxelCentersBySegment (
const Eigen::Vector3f& origin,
const Eigen::Vector3f& end,
AlignedPointTVector &voxel_center_list,
float precision)
{
Eigen::Vector3f direction = end - origin;
float norm = direction.norm ();
direction.normalize ();
const float step_size = static_cast<const float> (resolution_) * precision;
// Ensure we get at least one step for the first voxel.
const int nsteps = std::max (1, static_cast<int> (norm / step_size));
OctreeKey prev_key;
bool bkeyDefined = false;
// Walk along the line segment with small steps.
for (int i = 0; i < nsteps; ++i)
{
Eigen::Vector3f p = origin + (direction * step_size * static_cast<const float> (i));
PointT octree_p;
octree_p.x = p.x ();
octree_p.y = p.y ();
octree_p.z = p.z ();
OctreeKey key;
this->genOctreeKeyforPoint (octree_p, key);
// Not a new key, still the same voxel.
if ((key == prev_key) && (bkeyDefined) )
continue;
prev_key = key;
bkeyDefined = true;
PointT center;
genLeafNodeCenterFromOctreeKey (key, center);
voxel_center_list.push_back (center);
}
OctreeKey end_key;
PointT end_p;
end_p.x = end.x ();
end_p.y = end.y ();
end_p.z = end.z ();
this->genOctreeKeyforPoint (end_p, end_key);
if (!(end_key == prev_key))
{
PointT center;
genLeafNodeCenterFromOctreeKey (end_key, center);
voxel_center_list.push_back (center);
}
return (static_cast<int> (voxel_center_list.size ()));
}
void Camera::setRotate3D(const Eigen::Vector3f& rot) {
Eigen::AngleAxis<float> aaZ(rot.z(), Eigen::Vector3f::UnitZ());
Eigen::AngleAxis<float> aaY(rot.y(), Eigen::Vector3f::UnitY());
Eigen::AngleAxis<float> aaX(rot.x(), Eigen::Vector3f::UnitX());
rotation_future_ = aaZ * aaY * aaX;
emit modified();
}
/** Add a new point to the line string.
*/
void
MapLineString::addPoint(const Eigen::Vector3f& p)
{
// TODO: Automatically split arcs that cross the 180 degree meridian
m_points.push_back(p);
setBounds(bounds().extend(Vector2f(p.x(), p.y())));
}
Eigen::Vector3f RayTracer::findReflect(Eigen::Vector3f ray, Eigen::Vector3f normal, SceneObject* obj) {
Eigen::Vector3f reflectRay;
reflectRay = ray + (2.0*normal*(normal.dot(-ray)));
reflectRay.normalize();
return reflectRay;
}
/**
* Convert the global coordinates into camera space
* Multiply by pose.inverse()
* @param world_coordinate The 3D point in world space
* @return camera_coordinate The 3D pointin camera space
*/
Eigen::Vector3f Camera::world_to_camera( const Eigen::Vector3f & world_coordinate ) const {
using namespace Eigen;
Vector4f world_h { world_coordinate.x(), world_coordinate.y(), world_coordinate.z(), 1.0f};
Vector4f cam_h = m_pose_inverse * world_h;
return cam_h.block(0, 0, 3, 1) / cam_h[3];
}
/**
* Convert the camera coordinate into world space
* Multiply by pose
* @param camera_coordinate The 3D pointin camera space
* @return world_coordinate The 3D point in world space
*/
Eigen::Vector3f Camera::camera_to_world( const Eigen::Vector3f & camera_coordinate ) const {
using namespace Eigen;
Vector4f cam_h { camera_coordinate.x(), camera_coordinate.y(), camera_coordinate.z(), 1.0f};
Vector4f world_h = m_pose * cam_h;
return world_h.block(0, 0, 3, 1) / world_h.w();
}
Eigen::Vector2f PhotoCamera::project(const Eigen::Vector3f &point)
{
Eigen::MatrixXf P = intrinsicMatrix*extrinsicMatrix.matrix();
Eigen::Vector4f pointH;
pointH << point(0), point(1), point(2), 1;
Eigen::Vector3f pixelH = P*pointH;
return pixelH.hnormalized();
}
void stateCallback(const nav_msgs::Odometry::ConstPtr& state)
{
vel[0] = state->twist.twist.linear.x;
vel[1] = state->twist.twist.linear.y;
vel[2] = state->twist.twist.linear.z;
pos[2] = state->pose.pose.position.z;
//q.x() = state->pose.pose.orientation.x;
//q.y() = state->pose.pose.orientation.y;
//q.z() = state->pose.pose.orientation.z;
//q.w() = state->pose.pose.orientation.w;
float q_x = state->pose.pose.orientation.x;
float q_y = state->pose.pose.orientation.y;
float q_z = state->pose.pose.orientation.z;
float q_w = state->pose.pose.orientation.w;
float yaw = atan2(2*(q_w*q_z+q_x*q_y),1-2*(q_y*q_y+q_z*q_z));
//Eigen::Matrix3d R(q);
force(0) = offset_x+k_vxy*(vel_des(0)-vel(0))+m*acc_des(0);
if(pd_control==0)
force(1) = offset_y+k_vxy*(vel_des(1)-vel(1))+m*acc_des(1);
else if(pd_control==1)
{
pos[1]=state->pose.pose.position.y;
force(1) = offset_y+k_vxy*(vel_des(1)-vel(1))+k_xy*(0-pos[1])+m*acc_des(1);
}
force(2) = (k_z*(pos_des(2)-pos(2))+k_vz*(vel_des(2)-vel(2))+m*g(2)+m*acc_des(2));
b3 = force.normalized();
b2 = b3.cross(b1w);
b1 = b2.cross(b3);
R_des<<b1[0],b2[0],b3[0],
b1[1],b2[1],b3[1],
b1[2],b2[2],b3[2];
Eigen::Quaternionf q_des(R_des);
quadrotor_msgs::SO3Command command;
command.force.x = force[0];
command.force.y = force[1];
command.force.z = force[2];
command.orientation.x = q_des.x();
command.orientation.y = q_des.y();
command.orientation.z = q_des.z();
command.orientation.w = q_des.w();
command.kR[0] = k_R;
command.kR[1] = k_R;
command.kR[2] = k_R;
command.kOm[0] = k_omg;
command.kOm[1] = k_omg;
command.kOm[2] = k_omg;
command.aux.current_yaw = yaw;
command.aux.enable_motors = true;
command.aux.use_external_yaw = true;
control_pub.publish(command);
}
/** Update this line.
* @param linfo new info to consume
* This also updates moving averages for all fields.
*/
void TrackedLineInfo::update(LineInfo &linfo)
{
if (visibility_history <= 0)
visibility_history = 1;
else
visibility_history += 1;
this->raw = linfo;
fawkes::tf::Stamped<fawkes::tf::Point> bp_new(
fawkes::tf::Point(
linfo.base_point[0], linfo.base_point[1], linfo.base_point[2]
), fawkes::Time(0,0), input_frame_id);
try {
transformer->transform_point(tracking_frame_id, bp_new, this->base_point_odom);
} catch (fawkes::tf::TransformException &e) {
logger->log_warn(plugin_name.c_str(), "Can't transform to %s. Attempting to track in %s.",
tracking_frame_id.c_str(), input_frame_id.c_str());
this->base_point_odom = bp_new;
}
this->history.push_back(linfo);
Eigen::Vector3f base_point_sum(0,0,0), end_point_1_sum(0,0,0),
end_point_2_sum(0,0,0), line_direction_sum(0,0,0), point_on_line_sum(0,0,0);
float length_sum(0);
for (LineInfo &l : this->history) {
base_point_sum += l.base_point;
end_point_1_sum += l.end_point_1;
end_point_2_sum += l.end_point_2;
line_direction_sum += l.line_direction;
point_on_line_sum += l.point_on_line;
length_sum += l.length;
}
size_t sz = this->history.size();
this->smooth.base_point = base_point_sum / sz;
this->smooth.cloud = linfo.cloud;
this->smooth.end_point_1 = end_point_1_sum / sz;
this->smooth.end_point_2 = end_point_2_sum / sz;
this->smooth.length = length_sum / sz;
this->smooth.line_direction = line_direction_sum / sz;
this->smooth.point_on_line = point_on_line_sum / sz;
Eigen::Vector3f x_axis(1,0,0);
Eigen::Vector3f ld_unit = this->smooth.line_direction / this->smooth.line_direction.norm();
Eigen::Vector3f pol_invert = Eigen::Vector3f(0,0,0) - this->smooth.point_on_line;
Eigen::Vector3f P = this->smooth.point_on_line + pol_invert.dot(ld_unit) * ld_unit;
this->smooth.bearing = std::acos(x_axis.dot(P) / P.norm());
// we also want to encode the direction of the angle
if (P[1] < 0)
this->smooth.bearing = std::abs(this->smooth.bearing) * -1.;
Eigen::Vector3f l_diff = raw.end_point_2 - raw.end_point_1;
Eigen::Vector3f l_ctr = raw.end_point_1 + l_diff / 2.;
this->bearing_center = std::acos(x_axis.dot(l_ctr) / l_ctr.norm());
if (l_ctr[1] < 0)
this->bearing_center = std::abs(this->bearing_center) * -1.;
}
void Task::alignPointcloudAsMLS(const base::Time& ts, const std::vector< base::Vector3d >& sample_pointcloud, const envire::TransformWithUncertainty& body2odometry)
{
if(sample_pointcloud.size() == 0)
return;
boost::shared_ptr<envire::Environment> pointcloud_env;
pointcloud_env.reset(new envire::Environment());
envire::MLSProjection* pointcloud_projection = new envire::MLSProjection();
pointcloud_projection->useNegativeInformation(false);
pointcloud_projection->useUncertainty(true);
double grid_size = 200.0;
double cell_resolution = 0.1;
double grid_count = grid_size / cell_resolution;
envire::MultiLevelSurfaceGrid* pointcloud_grid = new envire::MultiLevelSurfaceGrid(grid_count, grid_count, cell_resolution, cell_resolution, -0.5 * grid_size, -0.5 * grid_size);
pointcloud_grid->getConfig().updateModel = envire::MLSConfiguration::KALMAN;
pointcloud_grid->getConfig().gapSize = 0.5;
pointcloud_grid->getConfig().thickness = 0.05;
pointcloud_env->attachItem(pointcloud_grid, pointcloud_env->getRootNode());
pointcloud_env->addOutput(pointcloud_projection, pointcloud_grid);
// create envire pointcloud
envire::Pointcloud* pc = new envire::Pointcloud();
pc->vertices.reserve(sample_pointcloud.size());
for(unsigned i = 0; i < sample_pointcloud.size(); i++)
pc->vertices.push_back(sample_pointcloud[i]);
// update mls
envire::MLSGrid* grid = pointcloud_projection->getOutput<envire::MLSGrid*>();
if(!grid)
{
RTT::log(RTT::Error) << "Missing mls grid in pointcloud environment." << RTT::endlog();
return;
}
grid->clear();
pointcloud_env->attachItem(pc, pointcloud_env->getRootNode());
pointcloud_env->addInput(pointcloud_projection, pc);
pointcloud_projection->updateAll();
// remove inputs
pointcloud_env->removeInput(pointcloud_projection, pc);
pointcloud_env->detachItem(pc, true);
// create pointcloud from mls_grid
PCLPointCloudPtr pcl_pointcloud(new PCLPointCloud());
createPointcloudFromMLS(pcl_pointcloud, grid);
// create debug pointcloud
aligned_cloud.points.clear();
aligned_cloud.colors.clear();
aligned_cloud.points.reserve(pcl_pointcloud->size());
for(unsigned i = 0; i < pcl_pointcloud->size(); i++)
{
Eigen::Vector3f point = pcl_pointcloud->at(i).getVector3fMap();
aligned_cloud.points.push_back(base::Vector3d(point.x(), point.y(), point.z()));
}
aligned_cloud.colors.resize(aligned_cloud.points.size(), base::Vector4d(1.0, 0.0, 0.0, 1.0));
alignPointcloud(ts, pcl_pointcloud, body2odometry);
}
Eigen::Vector3f FindObjectOnPlane::rayPlaneInteersect(
const cv::Point3d& ray,
const jsk_recognition_utils::Plane::Ptr& plane)
{
Eigen::Vector3f n = plane->getNormal();
Eigen::Vector3f d(ray.x, ray.y, ray.z);
double alpha = - plane->getD() / n.dot(d);
return alpha * d;
}
static void
write_calibration_parameter(
const Eigen::Vector3f &in_vector,
PSMoveProtocol::FloatVector *out_vector)
{
out_vector->set_i(in_vector.x());
out_vector->set_j(in_vector.y());
out_vector->set_k(in_vector.z());
}
