Location-based VR Tracking for All SteamVR Applications

09/03/2018
Blog
LPVR Pipeline Overview

UPDATE 1 – LPVR now offers VIVE Pro support!

UPDATE 2 – LPVR can now talk to all optical tracking systems that support VRPN (VICON, ART etc.).

UPDATE 3 – Of special interest to automotive customers may be that this also supports Autodesk VRED.

Current VR products cannot serve several important markets due to limitations of their tracking systems.  Out of the box, both the HTC Vive and the Oculus Rift are limited to tracking areas smaller than 5m x 5m, which is too small for most multi-player applications. We have previously presented our solution that combines our motion sensing IMU technology, OptiTrack camera-based tracking and the HTC Vive to allow responsive multiplayer VR experiences over larger areas. Because of the necessary interfacing this means that applications still need to be prepared specifically for this solution.

We have now further improved our software stack such that we can provide a SteamVR driver for our solution. What this means is that on the one hand any existing SteamVR application automatically supports the arbitrarily large tracking areas covered by the OptiTrack system. On the other hand it means that no additional plugins for Unity, Unreal or your development platform of choice is needed — support is automatic. Responsive behavior is guaranteed by using LP-RESEARCH’s IMU technology in combination with standard low-latency VR technologies like asynchronous time warping, late latching etc. An overview of the functionality of the system is shown in the image above.

LPMS-NAV Navigation Sensors for Mobile Robots and Automated Guided Vehicles (AGV)

26/09/2017
Product, Use Cases

We are proud to announce the release of a new series of high-precision sensors for applications in autonomous vehicle navigation. The sensors are based on quartz-vibration gyroscopes with low-noise, low-drift characteristics. They have excellent capabilities for measurement of slow to medium speed rotations.

We offer the new sensors in various versions with different communication interfaces and housing options: LPMS-NAV2, LPMS-NAV2-RS232 and LPMS-NAV2-RS422. Please check more detailed information on our products page

The following video shows a use-case of one of our customers in China. The company is using LPMS-NAV2-RS232 sensor for mobile robot navigation. Automatic navigation of automated guided vehicles (AGV) or cleaning robots are two of the principal application areas of the LPMS-NAV series.

If you have any interest in this product, please contact us for further information.

IMU-based Dead Reckoning (Displacement Tracking) Revisited

25/08/2017
Blog, Use Cases

IMU-Based Dead Reckoning Displacement Tracking Revisited

In a blog post a few years ago, we published results of our experiments with direct integration of linear acceleration from our LPMS-B IMU. At that time, although we were able to process data in close to real-time, displacement tracking only worked on one axis and for very regular up-and-down motions.

In the meantime the measurement quality of our IMUs has improved and we have put further work into researching dead reckoning applications. Fact is that still, low-cost MEMS as they are used in our LPMS-B2 devices are not suitable to perform displacement measurement for extended periods of time or with great accuracy. But, for some applications such as sports motion measurement or as one component in a larger sensor fusion setup, the results are very promising.

A further experiment shows this algorithm applied to the evaluation of boxing motions. This system might work as a base component for IoT boxing gloves that allow automatic evaluation of an athletes technique and strength, or it might ne integrated into an advanced controller for virtual reality sports.

As usual, please contact us for further information.

IMUcore Sensor Fusion

25/07/2017
Blog, Use Cases, カテゴリーなし

Introducing IMUcore

IMUcore is the central algorithm working inside all LP-RESEARCH IMUs. It collects orientation data from several sources and combines them into fast and drift-free tilt and direction information. To work with any type of MEMS sensor, various online and offline calibration methods have been implemented to guarantee high quality data output. The algorithm is very versatile and performance-saving. It can be implemented on embedded MCUs with minimum power consumption.

IMUcore is now available as a solution from LP-RESEARCH. Please contact us here for more information or a price quotation.

Overview of embedded sensor fusion in LPMS devices

Sensor Fusion Filter Overview

IMUcore uses gyroscope data as basis information to calculate orientation. Errors introduced through measurement noise are corrected by accelerometer and compass data. Optionally the sensor fusion can be extended with an optical (or other) tracking system to additionally provide position information.

All aspects of the IMUcore algorithm in one image

If this topic sounds familiar to you and you are looking for a solution to a related problem, contact us for further discussion.

Meet Xikaku

14/07/2017
Blog, Event

We are proud to present our new partner company Xikaku. Xikaku is a US company located in Los Angeles, focusing on the development of technology related to the field of augmented reality (AR). Visit their website here.

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