double compareT(Eigen::Isometry3d a, Eigen::Isometry3d b,
Eigen::VectorXd weight)
{
Eigen::Quaterniond qa(a.rotation());
Eigen::Quaterniond qb(b.rotation());
Eigen::Vector3d pa = a.translation();
Eigen::Vector3d pb = b.translation();
Eigen::VectorXd va(7), vb(7), verr(7), vScaled(7);
va << pa, qa.x(), qa.y(), qa.z(), qa.w();
vb << pb, qb.x(), qb.y(), qb.z(), qb.w();
verr = vb - va;
vScaled = weight.cwiseProduct(verr);
return vScaled.squaredNorm();
}
void VideoIMUFusion::RunningData::handleVideoTrackerReport(
const OSVR_TimeValue ×tamp, const OSVR_PoseReport &report) {
Eigen::Isometry3d roomPose = takeCameraPoseToRoom(report.pose);
#ifdef OSVR_FPE
FPExceptionEnabler fpe;
#endif
Eigen::Quaterniond orientation(roomPose.rotation());
auto oriChange = state().getQuaternion().angularDistance(orientation);
if (std::abs(oriChange) > M_PI / 2.) {
OSVR_DEV_VERBOSE("Throwing out a bad video pose");
return;
}
if (preReport(timestamp)) {
m_cameraMeasPos.setMeasurement(roomPose.translation());
osvr::kalman::correct(state(), processModel(), m_cameraMeasPos);
m_cameraMeasOri.setMeasurement(orientation);
osvr::kalman::correct(state(), processModel(), m_cameraMeasOri);
#if 0
OSVR_DEV_VERBOSE(
"State: " << state().stateVector().transpose() << "\n"
<< "Quat: "
<< state().getQuaternion().coeffs().transpose()
<< "\n"
"Error:\n"
<< state().errorCovariance());
#endif
}
}
pcl::PointCloud<pcl::PointXYZ>::Ptr Conversions::toPointCloud(const Eigen::Isometry3d &T, const image_geometry::PinholeCameraModel &cam, const cv::Mat &depth_img)
{
pcl::PointCloud<pcl::PointXYZ>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZ>());
cloud->header.frame_id = "cam";
cloud->is_dense = false;
cloud->height = depth_img.rows;
cloud->width = depth_img.cols;
cloud->sensor_origin_ = Eigen::Vector4f( T.translation()(0), T.translation()(1), T.translation()(2), 1.f );
cloud->sensor_orientation_ = Eigen::Quaternionf(T.rotation().cast<float>());
cloud->points.resize( cloud->height * cloud->width );
size_t idx = 0;
const float* depthdata = reinterpret_cast<float*>( &depth_img.data[0] );
for(int v = 0; v < depth_img.rows; ++v) {
for(int u = 0; u < depth_img.cols; ++u) {
pcl::PointXYZ& p = cloud->points[ idx ]; ++idx;
float d = (*depthdata++);
if (d > 0 && !isnan(d)) {
p.z = d;
p.x = (u - cam.cx()) * d / cam.fx();
p.y = (v - cam.cy()) * d / cam.fy();
} else {
p.x = std::numeric_limits<float>::quiet_NaN();
p.y = std::numeric_limits<float>::quiet_NaN();
p.z = std::numeric_limits<float>::quiet_NaN();
}
}
}
return cloud;
}
void print_Isometry3d(Eigen::Isometry3d pose, std::stringstream &ss){
Eigen::Vector3d t(pose.translation());
Eigen::Quaterniond r(pose.rotation());
ss <<t[0]<<", "<<t[1]<<", "<<t[2]<<" | "
<<r.w()<<", "<<r.x()<<", "<<r.y()<<", "<<r.z() ;
// std::cout << ss.str() << "q\n";
}
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr Conversions::toPointCloudColor(const Eigen::Isometry3d &T, DepthImageDataPtr depth_data)
{
pcl::PointCloud<pcl::PointXYZRGBA>::Ptr cloud(new pcl::PointCloud<pcl::PointXYZRGBA>());
cv::Mat depth_img;
cv::Mat color_img;
cv_bridge::CvImagePtr depth_bridge;
cv_bridge::CvImagePtr rgb_bridge;
try {
depth_bridge = cv_bridge::toCvCopy(depth_data->depth_image_, sensor_msgs::image_encodings::TYPE_32FC1);
depth_img = depth_bridge->image;
rgb_bridge = cv_bridge::toCvCopy(depth_data->color_image_, sensor_msgs::image_encodings::BGR8);
color_img = rgb_bridge->image;
} catch (cv_bridge::Exception& e) {
ROS_ERROR("cv_bridge exception: %s",e.what());
return cloud;
}
// Get camera info for 3D point estimation.
image_geometry::PinholeCameraModel cam = depth_data->camera_model_;
cloud->header.frame_id = depth_data->sensor_frame_;
cloud->is_dense = false;
cloud->height = depth_img.rows;
cloud->width = depth_img.cols;
cloud->sensor_origin_ = Eigen::Vector4f( T.translation()(0), T.translation()(1), T.translation()(2), 1.f );
cloud->sensor_orientation_ = Eigen::Quaternionf(T.rotation().cast<float>());
cloud->points.resize( cloud->height * cloud->width );
size_t idx = 0;
const float* depthdata = reinterpret_cast<float*>( &depth_img.data[0] );
const unsigned char* colordata = &color_img.data[0];
for(int v = 0; v < depth_img.rows; ++v) {
for(int u = 0; u < depth_img.cols; ++u) {
pcl::PointXYZRGBA& p = cloud->points[ idx ]; ++idx;
float d = (*depthdata++);
if (d > 0 && !isnan(d)/* && p.z <= 7.5*/) {
p.z = d;
p.x = (u - cam.cx()) * d / cam.fx();
p.y = (v - cam.cy()) * d / cam.fy();
cv::Point3_<uchar>* rgb = color_img.ptr<cv::Point3_<uchar> >(v,u);
p.b = rgb->x;
p.g = rgb->y;
p.r = rgb->z;
p.a = 255;
} else {
p.x = std::numeric_limits<float>::quiet_NaN();;
p.y = std::numeric_limits<float>::quiet_NaN();;
p.z = std::numeric_limits<float>::quiet_NaN();;
p.rgb = 0;
colordata += 3;
}
}
}
return cloud;
}
static Eigen::Affine3d toAffine(const Eigen::Isometry3d& pose)
{
Eigen::Affine3d p(pose.rotation());
p.translation() = pose.translation();
return p;
}
static inline void
print_isometry(const Eigen::Isometry3d & iso)
{
const Eigen::Vector3d & t = iso.translation();
Eigen::Vector3d rpy = _quat_to_roll_pitch_yaw(Eigen::Quaterniond(iso.rotation()))*180.0/M_PI;
fprintf(stderr, "trans:(% 6.3f % 6.3f % 6.3f) rot:(% 6.3f % 6.3f % 6.3f)",t(0),t(1),t(2),rpy(0),rpy(1),rpy(2));
// dbg("rot:(% 6.3f % 6.3f % 6.3f)",rpy(0),rpy(1),rpy(2));
}
std::string print_Isometry3d(Eigen::Isometry3d pose){
Eigen::Vector3d t(pose.translation());
Eigen::Quaterniond r(pose.rotation());
std::stringstream ss;
ss <<t[0]<<", "<<t[1]<<", "<<t[2]<<", "
<<r.w()<<", "<<r.x()<<", "<<r.y()<<", "<<r.z() ;
return ss.str();
}
// converts from a SE(3) Isometry transform to a 6D vector
inline Eigen::Matrix<double, 6, 1> fromIsometry(const Eigen::Isometry3d & T){
Eigen::Matrix<double, 6, 1> v;
v.block<3,1>(0,0) = T.translation();
Eigen::Quaterniond q(T.rotation());
q.normalize();
v.block<3,1>(3,0) = q.vec();
return v;
}
void print_Isometry3d(Eigen::Isometry3d pose, std::stringstream &ss){
Eigen::Vector3d t(pose.translation());
Eigen::Quaterniond r(pose.rotation());
double rpy[3];
quat_to_euler(r, rpy[0], rpy[1], rpy[2]);
ss <<t[0]<<", "<<t[1]<<", "<<t[2]<<" | "
<<r.w()<<", "<<r.x()<<", "<<r.y()<<", "<<r.z() << " | RPY "
<< rpy[0] <<", "<< rpy[1] <<", "<< rpy[2];
}
std::string
isometryToString(const Eigen::Isometry3d& m)
{
char result[80];
memset(result, 0, sizeof(result));
Eigen::Vector3d xyz = m.translation();
Eigen::Vector3d rpy = m.rotation().eulerAngles(0, 1, 2);
snprintf(result, 79, "%6.2f %6.2f %6.2f %6.2f %6.2f %6.2f",
xyz(0), xyz(1), xyz(2),
rpy(0) * 180/M_PI, rpy(1) * 180/M_PI, rpy(2) * 180/M_PI);
return std::string(result);
}
std::string print_Isometry3d(Eigen::Isometry3d pose){
Eigen::Vector3d t(pose.translation());
Eigen::Quaterniond r(pose.rotation());
double rpy[3];
quat_to_euler(r, rpy[0], rpy[1], rpy[2]);
std::stringstream ss;
ss <<t[0]<<", "<<t[1]<<", "<<t[2]<<", "
<<r.w()<<", "<<r.x()<<", "<<r.y()<<", "<<r.z() << ", "
<< rpy[0] <<", "<< rpy[1] <<", "<< rpy[2];
return ss.str();
}
bot_core::pose_t getPoseAsBotPose(Eigen::Isometry3d pose, int64_t utime){
bot_core::pose_t pose_msg;
pose_msg.utime = utime;
pose_msg.pos[0] = pose.translation().x();
pose_msg.pos[1] = pose.translation().y();
pose_msg.pos[2] = pose.translation().z();
Eigen::Quaterniond r_x(pose.rotation());
pose_msg.orientation[0] = r_x.w();
pose_msg.orientation[1] = r_x.x();
pose_msg.orientation[2] = r_x.y();
pose_msg.orientation[3] = r_x.z();
return pose_msg;
}
OdomTransPtr RGBDVisOdometry::Isometry3DToOdomTrans(Eigen::Isometry3d info)
{
Eigen::Vector3d xyz = info.translation();
Eigen::Vector3d rpy = info.rotation().eulerAngles(0, 1, 2);
OdomTransPtr odomInfo(new OdomTrans);
odomInfo->x = xyz(0);
odomInfo->y = xyz(1);
odomInfo->z = xyz(2);
odomInfo->alpha = rpy(0);
odomInfo->beta = rpy(1);
odomInfo->gamma = rpy(2);
return odomInfo;
}
void compute_velocity(const Eigen::Vector3d& v_parent,
const Eigen::Vector3d& w_parent,
const Eigen::Vector3d& v_rel,
const Eigen::Vector3d& w_rel,
const Eigen::Vector3d& offset,
const Eigen::Isometry3d& tf_parent,
Eigen::Vector3d& v_child,
Eigen::Vector3d& w_child)
{
const Eigen::Matrix3d& R = tf_parent.rotation();
v_child = v_parent + R*v_rel + w_parent.cross(R*offset);
w_child = w_parent + R*w_rel;
}
void App::doWork(){
std::vector<float> xA;
std::vector<float> yA;
readCSVFile(cl_cfg_.filenameA, xA, yA);
std::cout << xA.size() << " points in File A\n";
lidarOdom_->doOdometry(xA, yA, xA.size(), 0);
// Match second scan without a prior
std::string i;
cout << "Match B: Continue? ";
cin >> i;
std::vector<float> xB;
std::vector<float> yB;
readCSVFile(cl_cfg_.filenameB, xB, yB);
std::cout << xB.size() << " points in File B\n";
lidarOdom_->doOdometry(xB, yB, xB.size(), 1);
// Match third scan giving a prior rotation for the heading
// this alignment would otherwise fail:
cout << "Match C: Continue? ";
cin >> i;
std::vector<float> xC;
std::vector<float> yC;
readCSVFile(cl_cfg_.filenameC, xC, yC);
std::cout << xC.size() << " points in File C\n";
ScanTransform prior;
prior.x = 0;
prior.y = 0;
prior.theta = 1.7;
lidarOdom_->doOdometry(xC, yC, xC.size(), 2, &prior);
// 2. Determine the body position using the LIDAR motion estimate:
Eigen::Isometry3d pose = lidarOdom_->getCurrentPose();
Eigen::Quaterniond orientation(pose.rotation());
Eigen::Vector3d rpy = orientation.matrix().eulerAngles(0,1,2);
std::cout << "\n";
std::cout << "x,y,yaw (m,m,deg): "<< pose.translation().x() << ", " << pose.translation().y()
<< ", "
<< rpy[2]*180/M_PI << "\n";
}
void joints2frames::publishPose(Eigen::Isometry3d pose, int64_t utime, std::string channel){
if (!shouldPublish(utime, channel) )
return;
bot_core::pose_t pose_msg;
pose_msg.utime = utime;
pose_msg.pos[0] = pose.translation().x();
pose_msg.pos[1] = pose.translation().y();
pose_msg.pos[2] = pose.translation().z();
Eigen::Quaterniond r_x(pose.rotation());
pose_msg.orientation[0] = r_x.w();
pose_msg.orientation[1] = r_x.x();
pose_msg.orientation[2] = r_x.y();
pose_msg.orientation[3] = r_x.z();
lcm_->publish( channel, &pose_msg);
}
void joints2frames::publishRigidTransform(Eigen::Isometry3d pose, int64_t utime, std::string channel){
if (!shouldPublish(utime, channel) )
return;
bot_core::rigid_transform_t tf;
tf.utime = utime;
tf.trans[0] = pose.translation().x();
tf.trans[1] = pose.translation().y();
tf.trans[2] = pose.translation().z();
Eigen::Quaterniond quat(pose.rotation());
tf.quat[0] = quat.w();
tf.quat[1] = quat.x();
tf.quat[2] = quat.y();
tf.quat[3] = quat.z();
lcm_->publish(channel, &tf);
}
crazyflie_t::webcam_pos_t encodeWebcamPos(Eigen::Isometry3d const & frame)
{
Eigen::Vector3d t(frame.translation());
Eigen::Quaterniond r(frame.rotation());
Eigen::Vector3d rpy = quat_to_rpy(r);
crazyflie_t::webcam_pos_t msg;
msg.x = frame.translation().x();
msg.y = frame.translation().y();
msg.z = frame.translation().z();
msg.roll = rpy(0);
msg.pitch = rpy(1);
msg.yaw = rpy(2);
return msg;
}
crazytags::rigid_transform_t encodeLCMFrame(Eigen::Isometry3d const & frame)
{
Eigen::Vector3d t(frame.translation());
Eigen::Quaterniond r(frame.rotation());
crazytags::rigid_transform_t msg;
msg.quat[0] = r.w();
msg.quat[1] = r.x();
msg.quat[2] = r.y();
msg.quat[3] = r.z();
msg.trans[0] = t[0];
msg.trans[1] = t[1];
msg.trans[2] = t[2];
return msg;
}
inline
cv::Mat cvtIsometry_egn2ocv(const Eigen::Isometry3d& egn_o)
{
Eigen::Matrix3d eigenRotation = egn_o.rotation();
Eigen::Matrix<double,3,1> eigenTranslation = egn_o.translation();
cv::Mat R, t;
eigen2cv(eigenRotation, R);
eigen2cv(eigenTranslation, t);
t = t.reshape(1,3);
cv::Mat ocv_o = cv::Mat::eye(4,4,CV_64FC1);
R.copyTo(ocv_o(cv::Rect(0,0,3,3)));
t.copyTo(ocv_o(cv::Rect(3,0,1,3)));
return ocv_o;
}
Eigen::Isometry3d SmoothEstimatePropagator::SmoothPropagateAction::
exponencialInterpolation(const Eigen::Isometry3d& from, const Eigen::Isometry3d& to, double step) const
{
Eigen::Isometry3d res;
double maxdist = maxDistance-2;
// step goes from 1 to maxDistance, we need x from 0 to 1 in a linear way.
double x = 1 - ((maxdist - (step-1))/maxdist);
// alpha in [0, inf) describes the explonential ramp "steepness"
double alpha = 50;
// exponential ramp from 0 to 1
double exp_ramp = 1 - (x/(1+alpha*(1-x)));
// using quaternion representation and slerp for interpolate between from and to isometry transformations
res.linear() = (Eigen::Quaterniond(from.rotation()).slerp(exp_ramp, Eigen::Quaterniond(to.rotation()))).toRotationMatrix();
res.translation() = (1 - exp_ramp) * from.translation() + exp_ramp * to.translation();
return res;
}
void compute_acceleration(const Eigen::Vector3d& a_parent,
const Eigen::Vector3d& alpha_parent,
const Eigen::Vector3d& w_parent,
const Eigen::Vector3d& a_rel,
const Eigen::Vector3d& alpha_rel,
const Eigen::Vector3d& v_rel,
const Eigen::Vector3d& w_rel,
const Eigen::Vector3d& offset,
const Eigen::Isometry3d& tf_parent,
Eigen::Vector3d& a_child,
Eigen::Vector3d& alpha_child)
{
const Eigen::Matrix3d& R = tf_parent.rotation();
a_child = a_parent + R*a_rel
+ alpha_parent.cross(R*offset)
+ 2*w_parent.cross(R*v_rel)
+ w_parent.cross(w_parent.cross(R*offset));
alpha_child = alpha_parent + R*alpha_rel + w_parent.cross(R*w_rel);
}
void VoEstimator::publishPose(int64_t utime, std::string channel, Eigen::Isometry3d pose,
Eigen::Vector3d vel_lin, Eigen::Vector3d vel_ang){
Eigen::Quaterniond r(pose.rotation());
bot_core::pose_t pose_msg;
pose_msg.utime = utime;
pose_msg.pos[0] = pose.translation().x();
pose_msg.pos[1] = pose.translation().y();
pose_msg.pos[2] = pose.translation().z();
pose_msg.orientation[0] = r.w();
pose_msg.orientation[1] = r.x();
pose_msg.orientation[2] = r.y();
pose_msg.orientation[3] = r.z();
pose_msg.vel[0] = vel_lin(0);
pose_msg.vel[1] = vel_lin(1);
pose_msg.vel[2] = vel_lin(2);
pose_msg.rotation_rate[0] = vel_ang(0);
pose_msg.rotation_rate[1] = vel_ang(1);
pose_msg.rotation_rate[2] = vel_ang(2);
pose_msg.accel[0]=0; // not estimated or filled in
pose_msg.accel[1]=0;
pose_msg.accel[2]=0;
lcm_->publish( channel, &pose_msg);
}
bool poseEstimationDirect ( const vector< Measurement >& measurements, cv::Mat* gray, Eigen::Matrix3f& K, Eigen::Isometry3d& Tcw )
{
// 初始化g2o
typedef g2o::BlockSolver<g2o::BlockSolverTraits<6,1>> DirectBlock; // 求解的向量 顶点(姿态) 是6＊1的
DirectBlock::LinearSolverType* linearSolver = new g2o::LinearSolverDense< DirectBlock::PoseMatrixType > ();
DirectBlock* solver_ptr = new DirectBlock ( linearSolver );
// g2o::OptimizationAlgorithmGaussNewton* solver = new g2o::OptimizationAlgorithmGaussNewton( solver_ptr ); // G-N 高斯牛顿
g2o::OptimizationAlgorithmLevenberg* solver = new g2o::OptimizationAlgorithmLevenberg ( solver_ptr ); // L-M
g2o::SparseOptimizer optimizer;
optimizer.setAlgorithm ( solver );
optimizer.setVerbose( true );
// 添加顶点
g2o::VertexSE3Expmap* pose = new g2o::VertexSE3Expmap();//位姿
pose->setEstimate ( g2o::SE3Quat ( Tcw.rotation(), Tcw.translation() ) );//旋转矩阵 和 平移向量
pose->setId ( 0 );//id
optimizer.addVertex ( pose );//添加顶点
// 添加边
int id=1;
for ( Measurement m: measurements )
{
EdgeSE3ProjectDirect* edge = new EdgeSE3ProjectDirect (
m.pos_world,//3D 位置
K ( 0,0 ), K ( 1,1 ), K ( 0,2 ), K ( 1,2 ), gray//相机内参数 灰度图
);
edge->setVertex ( 0, pose );//顶点
edge->setMeasurement ( m.grayscale );//测量值为真是灰度值
edge->setInformation ( Eigen::Matrix<double,1,1>::Identity() );//误差 权重 信息矩阵
edge->setId ( id++ );
optimizer.addEdge ( edge );
}
cout<<"边的数量 edges in graph: "<<optimizer.edges().size() <<endl;
optimizer.initializeOptimization();//优化初始化
optimizer.optimize ( 30 );//最大优化次数
Tcw = pose->estimate();// 变换矩阵
}
Eigen::Matrix3d eigenRotation() const
{ return camera_transform.rotation(); }
Eigen::Vector2d isometry2distance(const Eigen::Isometry3d& t) {
return Eigen::Vector2d(t.translation().norm(),
fabs(Eigen::AngleAxisd(t.rotation()).angle()));
}
bool setChannels(const std::string& iInputChannel,
const std::string& iOutputChannel) {
if (mSubscription != NULL) {
mLcm->unsubscribe(mSubscription);
}
mInputChannel = iInputChannel;
mOutputChannel = iOutputChannel;
BotCamTrans* inputCamTrans =
bot_param_get_new_camtrans(mBotWrapper->getBotParam(),
mInputChannel.c_str());
if (inputCamTrans == NULL) {
std::cout << "error: cannot find camera " << mInputChannel << std::endl;
return false;
}
BotCamTrans* outputCamTrans =
bot_param_get_new_camtrans(mBotWrapper->getBotParam(),
mOutputChannel.c_str());
if (outputCamTrans == NULL) {
std::cout << "error: cannot find camera " << mOutputChannel << std::endl;
return false;
}
int inputWidth = bot_camtrans_get_width(inputCamTrans);
int inputHeight = bot_camtrans_get_height(inputCamTrans);
mOutputWidth = bot_camtrans_get_width(outputCamTrans);
mOutputHeight = bot_camtrans_get_height(outputCamTrans);
// precompute warp field
mWarpFieldIntX.resize(mOutputWidth*mOutputHeight);
mWarpFieldIntY.resize(mWarpFieldIntX.size());
mWarpFieldFrac00.resize(mWarpFieldIntX.size());
mWarpFieldFrac01.resize(mWarpFieldIntX.size());
mWarpFieldFrac10.resize(mWarpFieldIntX.size());
mWarpFieldFrac11.resize(mWarpFieldIntX.size());
Eigen::Isometry3d outputToInput;
if (!mBotWrapper->getTransform(mOutputChannel, mInputChannel,
outputToInput)) {
std::cout << "error: cannot get transform from " << mOutputChannel <<
" to " << mInputChannel << std::endl;
return false;
}
Eigen::Matrix3d rotation = outputToInput.rotation();
Eigen::Vector3d ray;
for (int i = 0, pos = 0; i < mOutputHeight; ++i) {
for (int j = 0; j < mOutputWidth; ++j, ++pos) {
mWarpFieldIntX[pos] = -1;
if (0 != bot_camtrans_unproject_pixel(outputCamTrans, j, i,
ray.data())) {
continue;
}
ray = rotation*ray;
double pix[3];
if (0 != bot_camtrans_project_point(inputCamTrans, ray.data(), pix)) {
continue;
}
if ((pix[2] < 0) ||
(pix[0] < 0) || (pix[0] >= inputWidth-1) ||
(pix[1] < 0) || (pix[1] >= inputHeight-1)) {
continue;
}
mWarpFieldIntX[pos] = (int)pix[0];
mWarpFieldIntY[pos] = (int)pix[1];
double fracX = pix[0] - mWarpFieldIntX[pos];
double fracY = pix[1] - mWarpFieldIntY[pos];
mWarpFieldFrac00[pos] = (1-fracX)*(1-fracY);
mWarpFieldFrac01[pos] = (1-fracX)*fracY;
mWarpFieldFrac10[pos] = fracX*(1-fracY);
mWarpFieldFrac11[pos] = fracX*fracY;
}
}
mLcm->subscribe(mInputChannel, &ImageWarper::onImage, this);
return true;
}