Lighthouse Sensor Schematics

Basic information on Lighthouse and schematics

Schematics of the discrete part of a sensor node for the Valve/HTC Vive Lighthouse Tracking System courtesy of Alan Yates. More info in this thread on reddit: reddit.com/r/Vive/comments/465lqw/lighthouse_sensor_module_designs/ in Alan Yates posts here: reddit.com/user/vk2zay and in this video with him talking about it at maker faire:

Also interesting the embedded-fm podcast with Alan Yates talking about Lighthouse Development and the science behind it in general: http://embedded.fm/episodes/162

In depth analysis of lighthouse technology

For an in depth analysis of the lighthouse system read Oliver Kreylos post here: doc-ok.org

lighthouse-sensor

Someone made a board from the schematics. The data is on github: github.com/pdaderko/lighthouse_sensor/tree/master/hardware

lighthouse-node-pcb

Open Source implementation

There is a open source implementation of a indoor tracking system that uses the vive base stations on github: https://github.com/ashtuchkin/vive-diy-position-sensor

Official Licensing of Lighthouse Technology

Last but not least. Valve started a royalty-free licensing program to use lighthouse technology for third-party products. Licensees will need to pay $2,975 to attend a training course, but other than that, there’s no licensing fees or royalties for using the tech.

Valve provides a Lighthouse ‘Licensee Dev Kit’ to companies who apply to use the technology. It includes:

Dev Kit Contents

  • A modular reference tracked object suitable for attaching to prototype HMDs or other devices
  • Full complement of EVM circuit boards to enable rapid prototyping of your own tracked object
  • 40 individual sensors for building your own tracked object
  • Accessories to enable custom prototypes

Tools

  • Software toolkit to assist with optimal sensor placement
  • Calibration tools for prototyping and manufacturing

Documentation

  • Schematics and layouts for all electronic components
  • Mechanical designs for the reference tracked object and accessories
  • Datasheets for the sensor ASICs
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Mobile 3D Augmented Reality – Project Tango

I remember when the Kinect was first released, and later when the first 3D AR demos leveraging Kinect Fusion style algorithms became public, thinking that this would be a very interesting thing to have on a mobile platform.

Now Google has made its Project Tango public that is promising to deliver exactly this.

tango-phone

Their protoype a 5″ phone is capable of tracking full 3D motion while simultaneously creating a 3D map of its environment. Running on Android APIs provide position, orientation, and depth data to standard Android applications written in Java, C/C++, as well as the Unity Game Engine.

Algorithms, and APIs are still in active development. You can apply for a developer program to receive one of the 200 prototype device currently available. They expect to distribute all of our their available units by March 14th, 2014.

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Realtime Train and Bus Tracking in Berlin

Link

Berlin has launched a Open Street Map based service that shows in realtime positions of public transport train and bus traffic. The display of busses is turned of by default. Check the respective box in the “Fahrten” column to turn it on.

The regular journey planer for the Berlin public transport is at: http://www.bvg.de/, and for mobile there are the fantastic official BVG Apps for iOS and Android

bvg-live

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WiFi Based Visitor Tracking

On re:publica 2013 the Berlin based german data designers from OpenDataCity created a wifi tracking network with 100 Access Points that allowed them to visualize the movements of about 6,700 different electronic devices during the conference.

The application called re:log is a dynamic map of the conference location that shows the approximate locations of the devices when they were connected to the local WiFi hotspots. An interactive timeline underneath allows to explore the dynamic changes over time, while a rectangular area can be drawn to more specifically highlight and follow a smaller amount of dots.

The visualization was based on tracking the MAC addresses of the devices according to the WiFi hotspot they were connected to. This data, which can be downloaded, was fully anonymized, yet the authors mention their desire to allow people to look up their own MAC address in the future.

I suspect the solution used is based on MagicMap a free Wifi/Bluetooth tracking architecture developed at the Humboldt-University Berlin. Their Wiki has some more information.

relog-app

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Open Source Kinect Fusion – Update

There is an update on the open source implementation of Microsofts Kinect Fusion Algorithm by developers of the open source Point Cloud Library.

They improved on the Microsoft implementation with their algo called KinFu Large as they are able to scan multiple volumes in on pass allowing to scan larger scenes in one go.

The point cloud library (PCL) is available as prebuild binaries for Linux, Windows and OSX as well as in source code from their svn repository. The code relies heavily on the NVidia CUDA development libraries for GPU optimizations and will require a compatible GPU for best results. Information on how to setup your own build environment and the required dependencies is available from their site.

Besides the Kinect the library supports several other sensor via OpenNi.

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