Augmented reality (AR) provides a natural interface to the "calm" pervasive technology anticipated in large-scale ubiquitous computing environments. However, the range of classic AR applications has been limited by the scope, range and cost of sensors used for tracking. Hybrid tracking approaches can go some way to extending this range. We propose an approach, called ubiquitous tracking, in which data from widespread and diverse heterogeneous tracking sensors is automatically and dynamically fused, and then transparently provided to applications. A formal model represents spatial relationships between objects as a graph attributed with quality-of-service parameters. This paper presents a software implementation, in which a dynamic data flow network of distributed software components is thereby constructed in response to queries and optimisation criteria specified by applications. This implementation is demonstrated using a small laboratory example, and larger setups modelled in a simulation environment.

Augmented reality research currently aims at extending the working range of applications by combining multiple trackers in adjacent areas. The transition between two such devices leads to discontinuities in the trajectory of a tracked object. The result are "jumps" in visual augmentations shown to the user. We present a three step unsupervised learning algorithm that determines the working areas of involved trackers and the area they overlap, and permanently observes the tracked object's position with regard to these areas in order to enable a smooth interpolation within the overlapping area from one tracker's readings to another's. We have tested the algorithm's performance in an experimental setup. The results show that the method is feasible and only adds a negligible overhead to AR systems.

In the past, architectures of augmented reality systems have been widely different and tailored to specific tasks. In this paper, we use the example of the SHEEP game to show how the structural flexibility of DWARF, our component-based distributed wearable augmented reality framework, facilitates a rapid prototyping and online development process for building, debugging and altering a complex, distributed, highly interactive AR system. The SHEEP system was designed to test and demonstrate the potential of tangible user interfaces which dynamically visualize, manipulate and control complex operations of many inter-dependent processes. SHEEP allows the users more freedom of action and forms of interaction and collaboration, following the tool metaphor that bundles software with hardware in units that are easily understandable to the user. We describe how we developed SHEEP, showing the combined evolution of framework and application, as well as the progress from rapid prototype to final demonstration system. The dynamic aspects of DWARF facilitated testing and allowed us to rapidly evaluate new technologies. SHEEP has been shown successfully at various occasions. We describe our experiences with these demos.