DaStrasser

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Bootstrapping of Sensor Networks in Ubiquitous Tracking Environments

Student: Franz Strasser
Supervisors: Martin Bauer, Asa MacWilliams, Martin Wagner
Professor: Prof. Gudrun Klinker
Deadline: July 15th, 2004

Part of the Ubitrack Project

Final Version Download

The final version of my diploma thesis: DAStrasser.pdf
Presentation slides: slides.pdf

Abstract of my work

Augmented Reality (AR) applications fuse the real and the virtual world together. Tracking of real objects is a major part of any AR application because it must know their spatial relationships to interact with the user. Ubiquitous Computing applications try to integrate intelligent devices into the environment. By combining concepts of Ubiquitous Computing and Augmented Reality, tracking technologies can be dynamically integrated in new applications. Ubiquitous Tracking aggregates different trackers into one sensor network where all different types of mobile and stationary sensors contribute to the whole system.

This thesis deals with the integration of mobile tracking set-ups (clients) into stationary or mobile ones. The client itself does not have any initial knowledge of its ambient infrastructure. The focus of this thesis is to find a conceptual component-based model for dynamically integrating the mobile clients into large-scale sensor networks. In order to accomplish this in a scalable way, the network has to be divided into smaller, self-manageable parts, e.g. by introducing a hierarchical location context.

I analyze the requirements for a Ubiquitous Tracking system and give a complete overview over all possible scenarios where two separated systems get connected at runtime. The assumption is that at least one of them is a mobile set-up which has no initial knowledge of the other. By exchanging configuration, information the two systems can (re-)configure their hardware equipment to enable the tracking of each other. If this information does not describe the whole sensor network completely, the sensors can merely track unknown objects.

One of the major issues is to recognize and identify these unknown objects by their own motion patterns. By investigating the speed and angular velocity of two objects from two different trackers, static relationships between them can be discovered without an actual measurement of a sensor. The main idea is to find correlation by analyzing the frequencies of those two values.

I present results of the investigation of different tracking technologies, such as the ART tracking system, ARToolKit and Intersense. They show how far these sensors are suitable for the frequency analysis.

Proposal

PDF version of the proposal
Slides of the presentation

Old Introduction (obsolete)

For the old intruduction see here.

Project Schedule

Until workshop List of abstracts of all relevant papers concerning:
- P2P architectures
- Forming P2P sensor networks
- Routing through these networks
- Motion estimation (together with Daniel)
Post the list in the TWiki web
Ubitrack workshop Present results of literature search
Define hardware API with project members
February - march Implement needed extensions to the middleware
Simulate P2P system in simulator
March - april Form real SR graph over subnetwork boundaries
Fallback: Use a only one subnet where all nodes reside
Realize parts of the scenario in a first demo
April - may Integration with the components of Dagmar and Daniel
Final Demo !
May Write thesis

-- FranzStrasser - 30 Jan 2004

ProjectForm
Title: Bootstrapping of Sensor Networks in Ubiquitous Tracking Environments
Abstract: Augmented Reality (AR) applications fuse the real and the virtual world together. Tracking of real objects is a major part of any AR application because it must know their spatial relationships to interact with the user. Ubiquitous Computing applications try to integrate intelligent devices into the environment. By combining concepts of Ubiquitous Computing and Augmented Reality, tracking technologies can be dynamically integrated in new applications. Ubiquitous Tracking aggregates different trackers into one sensor network where all different types of mobile and stationary sensors contribute to the whole system. This thesis deals with the integration of mobile tracking set-ups (clients) into stationary or mobile ones. The client itself does not have any initial knowledge of its ambient infrastructure. The focus of this thesis is to find a conceptual component-based model for dynamically integrating the mobile clients into large-scale sensor networks. In order to accomplish this in a scalable way, the network has to be divided into smaller, self-manageable parts, e.g. by introducing a hierarchical location context. I analyze the requirements for a Ubiquitous Tracking system and give a complete overview over all possible scenarios where two separated systems get connected at runtime. The assumption is that at least one of them is a mobile set-up which has no initial knowledge of the other. By exchanging configuration, information the two systems can (re-)configure their hardware equipment to enable the tracking of each other. If this information does not describe the whole sensor network completely, the sensors can merely track unknown objects. One of the major issues is to recognize and identify these unknown objects by their own motion patterns. By investigating the speed and angular velocity of two objects from two different trackers, static relationships between them can be discovered without an actual measurement of a sensor. The main idea is to find correlation by analyzing the frequencies of those two values. I present results of the investigation of different tracking technologies, such as the ART tracking system, ARToolKit? and Intersense. They show how far these sensors are suitable for the frequency analysis.
Student: Franz Strasser
Director: Gudrun Klinker
Supervisor: Martin Bauer, Martin Wagner, Asa MacWilliams
Type: Diploma Thesis
Status: finished
Start:  
Finish: 2004/07/15


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