diploma thesis inaugural lecture: sensor-driven indoor-localization/-navigation
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Diploma Thesis Inaugural Lecture: Sensor-Driven Indoorlocalization and IndoornavigationTRANSCRIPT
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Stephan Linzner & Daniel Kersting
Diploma Thesis Inaugural Lecture
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Who we are
Stephan Linzner
Student, fifth year
major in computer
science at University
Tübingen
http://twitter.com/onlythoughtwork
Daniel Kersting
Student, fifth year
major in computer
science at University
Tübingen
http://twitter.com/drewenut
Diploma thesis: Sensor-driven indoor-localisation/-navigation with Android OS 2
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Lost Indoors
Diploma thesis: Sensor-driven indoor-localisation/-navigation with Android OS 3
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Lost Indoors…
Shopping center Product search
CBR (Consumer Based Routing)
IBR (Interest Based Routing)
Museums Family quiz, navitainment
Fairs i.e. CEBIT
Car park, airport, subway, concert hall, sewerages
Emergency evacuation and guidance service Fire, earthquake, terror attacks
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Motivation
Common outdoor navigation systems
are freely available today.
GPS is based on satellite networks and
can therefore only be used outdoors.
Today there is no ubiquitous localization
and navigation system for confined
spaces.
20 million sensor powered handsets
sold in 2008.
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Key questions
What are use cases to be handled?
How to create a data model of confined spaces?
Which (sensor) data is required?
Where could that data come from?
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Objectives of our work (1)
Evaluate methods and practices to realize a real-time sensor-driven indoor positioning system (SD-IPS) for mobile handsets.
Develop innovative approaches for mapping the most common characteristics of outdoor navigation systems to indoor application scenarios and expand them by dedicated confined spaces requirements.
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Objectives of our work (2)
Create an Android based application framework to easily build sensor-driven indoor positioning applications. Rely as much as possible on standard handset
hardware and not heavily depend on environment infrastructure.
Keep a lightweight design approach for concepts and the resulting framework.
Deliver augmented reality end user experience to make peoples indoor lifeseasier.
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Framework objectives
Lightweight design
Portable (iPhone, Symbian OS, RIM)
Blackboxed
Focused on data providing
Data representation
SD-IPS API
Not a GUI framework
No data visualization
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Initial schedule
June 2009 – dig through sources Android
Kernel
Drivers
Libraries (Zxing)
July/August 2009 – try and research Test and evaluate the sensors
Localization by 2D codes
Explore possibilities (WLAN, Bluetooth…)
Build the first prototypes
September/October 2009 – implement framework
November 2009 – elaboration
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What is Android?
Mobile operating system
Linux kernel version 2.6.x
Middleware
Application framework
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Why Android?
Open
All applications are created equal
Breaking down application boundaries
Fast & easy application development
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Rooted Android Developer Handset
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Android Developer Handset Sensors
Accelerometer
Gyroscope
Compass (Magnetic Field)
Camera (Imaging, scanning 2D-Barcodes)
GPS
Radio Network
WLAN
Bluetooth
Audio (Microphone)
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Inertial Navigation Set (IRBM S3)
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6-axis electronic compass (G1)
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Asahi Kasei Microsystems
(AKM) AK8976A
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Technologies vs. Techniques (1)
Ambient technologies
WLAN
○ Trilateration
○ Time of arrival (ToA)
○ Received signal strength (RSSI)
Bluetooth
○ Received signal strength (RSSI)
Audio
○ Echo
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Technologies vs. Techniques (2)
Optical technologies Camera
○ Visual detection
○ Augmented reality
○ 2D Barcodes Data Matrix
QR-Codes
Microelectromechanical technologies Sensors
○ Accelerometer
○ Gyroscope
○ Magnetic Field
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Localization/Positioning Techniques
No infrastructure No additional hardware needed
Infrastructure Based Environmental hardware needed
Marker based localization Fixed synchronization points
Inertial navigation
Dead reckoning
Continuous localization Real-time position tracking
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Localization/Positioning
Techniques (2)
Infrastructure No Infrastructure
Marker based • Wlan
• Bluetooth
• Audio
• Camera
Continuous • Wlan
• Bluetooth
• Audio
• Bluetooth
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Navigation Techniques
Inertial Navigation
Accelerometer
Gyroscope
Compass (Magnetic field)
Dead reckoning (DR)
Process of estimating one's current position
based upon a previously determined position
Estimate position by speeds over elapsed time
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Accelerometer/* x<0 x>0
* ^
* |
* +-----------+--> y>0
* | |
* | |
* | |
* | | / z<0
* | | /
* | | /
* O-----------+/
* |[] [ ] []/
* +----------/+ y<0
* /
* /
* |/ z>0 (toward the sky)
*
* O: Origin (x=0,y=0,z=0)
*/
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Gyroscope Z-Rotation
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Gyroscope X-Rotation
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Gyroscope Y-Rotation
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Responsibilities
Localization
Framework design
Domain modeling
Reusability
Navigation
Framework design
Platform independency
Portability
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Stephan Linzner Daniel Kersting
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Summary
Comprehensive exploration of the Android operating system and the SDK.
Requires solid Java and C knowledge
Identify indoor localization and navigation key concepts.
Implement the most promising solution, which delivers the best trade of between accuracy, efficiency and usability, for the desired scenarios in a conceptual framework.
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Future Prospects (1)
Visualization framework
Augmented reality framework
Wikitude:
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Future Prospects (2)
Routing algorithms
Consumer based routing (CBR)
Interest based routing (IBR)
Proximity based applications
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