olzhas

https://github.com/aancel/admin/wiki/VirtualGL-on-Ubuntu

https://virtualgl.org/About/Introduction

https://www.turbovnc.org

VirtualGL

When you use ssh with X forwarding, you might have noticed that you cannot execute programs that require 3D acceleration. That's where VirtualGL comes into play.

olzhas

To forward X11 from inside a docker container to a host running macOS

1. Install XQuartz: https://www.xquartz.org/
2. Launch XQuartz. Under the XQuartz menu, select Preferences
3. Go to the security tab and ensure "Allow connections from network clients" is checked.
4. Run xhost + ${hostname} to allow connections to the macOS host *
5. Setup a HOSTNAME env var export HOSTNAME=`hostname`*
6. Add the following to your docker-compose:

 environment:

olzhas

The document provides description on calibration of three Kinect for Microsoft sensors connected to one computer with several usb controllers. Three cameras setup is shown below:

Intrinsic, extrinsic, and Kinect2Kinect calibration is performed to know the position of each sensor in the space. Our setup is ROS Indigo with Ubuntu 14.04. freenect_launch and camera_pose ROS packages are used. Camera_pose package provides the pipeline to calibrate the relative 6D poses between multiple camera's. freenect_launch package contains launch files for using OpenNI-compliant devices in ROS. It creates a nodelet graph to transform raw data from the device driver into point clouds, disparity images, and other products suitable for processing and visualization. It is installed with catkin as follows:

# Prepa

olzhas

import numpy as NP
import casadi as C
def qpsolve(H,g,lbx,ubx,A=NP.zeros((0,0)),lba=NP.zeros(0),uba=NP.zeros(0)):
    # Convert to CasADi types
    H = C.DMatrix(H)
    g = C.DMatrix(g)
    lbx = C.DMatrix(lbx)
    ubx = C.DMatrix(ubx)
    A = C.DMatrix(A)
    A = A.reshape((A.size1(),H.size1())) # Make sure matching dimensions

olzhas

#include <Eigen/Dense>

template <class MatT>
Eigen::Matrix<typename MatT::Scalar, MatT::ColsAtCompileTime, MatT::RowsAtCompileTime>
pseudoinverse(const MatT &mat, typename MatT::Scalar tolerance = typename MatT::Scalar{1e-4}) // choose appropriately
{
    typedef typename MatT::Scalar Scalar;
    auto svd = mat.jacobiSvd(Eigen::ComputeFullU | Eigen::ComputeFullV);
    const auto &singularValues = svd.singularValues();
    Eigen::Matrix<Scalar, MatT::ColsAtCompileTime, MatT::RowsAtCompileTime> singularValuesInv(mat.cols(), mat.rows());