Virtual Dashboard Demonstration
This is a follow-up post to the introduction of our in-vehicle AR head mounted display LPVIZ part 1 and part 2.
To test LPVIZ we created a simple demo scenario of an automotive virtual dashboard. We created a Unity scene with graphic elements commonly found on a vehicle dashboard. We animated these elements to make the scene look more realistic.
This setup is meant for static testing at our shop. For further experiments inside a moving vehicle we are planning to connect the animated elements directly to car data (speed etc.) communicated over the CAN bus.
The virtual dashboard is only a very simple example to show the basic functionality of LPVIZ. As described in a previous post, many a lot more sophisticated applications can be implemented.
The video above was taken through the right eye optical waveguide display of LPVIZ. We took this photo with a regular smartphone camera and therefore it is not very high quality. Nevertheless, it confirms that the display is working and correctly shows the virtual dashboard.
The user is looking at the object straight ahead. In case the user rotates his head or changes position, his view of the object will change perspectively. An important point to mention is the high luminosity of the display. We took this photo with the interior lighting in our shop turned on normally, and without any additional shade in front of the display.
Introduction
LabView by National Instruments (NI) is one of the most popular multi-purpose solutions for measurement and data acquisition tasks. A wide range of hardware components can be connected to a central control application running on a PC. This application contains a full graphical programming language that allows the creation of so called virtual instruments (VI).
Data can be acquired inside a LabView application via a variety of communication interfaces, such as Bluetooth, serial port etc. A LabView driver that can communicate with our LPMS units has been a frequently requested feature from our customers for some time, so that we decided to create this short example to give a general guideline.
A Simple Example
The example shown here specifically works with LPMS-B2, but it is easily customizable to work with other sensors in our product line-up. In order to communicate with LPMS-B2 we use LabView’s built-in Bluetooth access modules. We then parse the incoming data stream to display the measured values.
The source code repository for this example is here.
Figure 1 – Overview of a minimal virtual instrument (VI) to acquire data from LPMS-B2
Fig. 1 shows an overview of the example design to acquire the accelerometer X, Y, Z axes of the IMU and displays them on a simple front panel. Fig. 2 & 3 below show the virtual instrument in more detail. After reading out the raw data stream from the Bluetooth interface, this data stream is converted into a string. The string is then evaluated to find the start and stop character sequence. The actual data is finally extracted depending on its position in the data packet.
Figure 2 – Bluetooth access and initial data parsing
Figure 3 – Extraction of timestamp, accelerometer X, Y, Z values
Notes
Please note that the example requires manually entering the Bluetooth ID of the LPMS-B2 in use. The configuration of the data parsing is static. Therefore the output data of the sensor needs to be configured and saved to sensor flash memory in the LPMS-Control application. For reference please check the LPMS manual.
An initial version of this virtual instrument was kindly provided to us by Dr. Patrick Esser, head of the Movement Science Group at Oxford Brooks University, UK.
We are happy to announce a collaboration with the head-mounted display (HMD) manufacturer Pimax. Pimax HMDs feature very high resolution (up to 8K pixels) displays and an industry-leading field-of-view (max. 200°). By default, Pimax HMDs support SteamVR tracking and therefore are limited to relatively small tracking volumes.
We developed a special driver that allows our LPVR middleware LPVR-CAD and LPVR-DUO to work with Pimax headsets. Using LPVR, the headsets can now be used within a large-scale, location-based context, in connection with outside-in optical systems such as ART (Advanced Real-Time Tracking).
As Pimax is planning to implement UltraLeap hand tracking in their HMDs in the future, we are confident that we will also be able to extend our inside-out tracking algorithm to their devices.
The video above shows the basic functionality of tracking a Pimax HMD using LPVR and an optical tracking system. The headset’s motions are represented in SteamVR. For this demonstration the tracking volume is relatively small, but can be extended easily by using more outside-in tracking cameras.
This video was kindly provided to us by evoTec Solutions. Evotec is a new company in Switzerland that focuses on virtual reality (VR) solutions for corporations. Contact them for further information!
