A software developer with the alias jericho has released JNA based Java bindings for the newly released Oculus Rift 0.4.2.0 SDK.

It is available from his github page.

Prebuilt jars are available from the maven repository (.dlls are embedded)

Here is a simple WebSocket server I’ve wrote that provides clients with the tracking info:

Now go code some awsome Oculus demoes 😉

Below you’ll find an example of a Python WebSocket client that receives and shows a image that it gets from a Python WebSocket server.

The example is quite simple, and is just an example of how you could send a image over a WebSocket connection.

Continue reading Sending images over websockets in Python 2.7 →

In this guide we are going to install the following:

And it’s dependencies:

Continue reading Installing PyFMI 1.5 on Ubuntu 14.04 →

In classic kinematics, the Jacobian is used to solve the inverse velocity kinematics.

The forward kinematics equation is given by \( \quad x = f(\theta) \)and the Jacobian matrix is a linear approximation to \(f\).

$$J(\theta) = \begin{bmatrix} \frac{\partial p_x}{\partial \theta_1} & \frac{\partial p_x}{\partial \theta_2} & … & \frac{\partial p_x}{\partial \theta_n} \\[0.3em] \frac{\partial p_y}{\partial \theta_1} & \frac{\partial p_y}{\partial \theta_2} & … & \frac{\partial p_y}{\partial \theta_n} \\[0.3em] … & … & … & … \\[0.3em] \frac{\partial a_z}{\partial \theta_1} & \frac{\partial a_z}{\partial \theta_2} & … & \frac{\partial a_z}{\partial \theta_n} \end{bmatrix}$$

Continue reading Numerically determinate the manipulator Jacobian →

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