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Interactive Visual Decision Support Systems

Miroslav Andel and Matthew Cooper

NVIS has had considerable success in the development of new visualization and interaction methods and have found that, for complex time-based data, these approaches can provide great insight. This approach has proven, for example, to be useful in system identification where we have used VR display and interaction systems to enable pattern identification in long time series. In this project we will address new 3D and 4D interaction mechanisms, based on VR technologies, for the visualization of dynamic data.

 Our target application here is decision support in the realm of active control of flight information. Previous work in this area by NVIS has focussed on the management of commercial fligth traffic but, within this project, we will focus on the control of, and the interpretation of data retrieved from, multiple unmanned air vehicles. VR systems can provide a powerful approach to the visualization of complex multidimensional data since interaction modes can be created to correspond with the data under consideration and can be modified as required as the user switches from task to task.  

The real-time system we propose for the UAV project will provide a visualization system to review terrain for the UAV mission. Flight plans will be configured by direct plotting of trajectories through 'way-points' according to the features found in the terrain. The flight plans can then be transferred to the UAV(s) for the mission before the mission commences. The in-flight UAV data can then be visualized, in real-time, as they are received, and the progress of the aircraft can be reviewed in comparison with the planned mission data. The new data received from the sensors on each aircraft can also be immediately reviewed within the same visualization environment and mission parameters will be adjusted in response to the terrain and other data received. This fusion of the exisiting terrain data and the new information coming from the UAV sensors, as well as other sources, will require a sophisticated blending of data with consideration of the many levels of detail in the various information sources as well as of the limitations of the channels by which the data are delivered, such as error rates, data omission and other potential sources of error.