Jerzy Rozenblit, a professor of Electrical and Computer Engineering at the University of Arizona in Tucson, is developing 3-D decision support software to help field commanders visualise the battlespace for combined land, sea and air operations.
‘We call it symbolic visualisation because our purpose is to create new visualisation concepts that are different from high-resolution displays that create photo-like simulations,’ Rozenblit said.
‘Here our approach is the opposite of realistic-looking, high-resolution displays. We are using a set of abstract symbols that are quite simple in terms of how they are depicted, yet have rich semantics behind them.’
A battalion, for instance, might be represented by a cube, which has five usable sides, the sixth side being its connection to the underlying terrain. The cube represents the unit, but each side could carry information about such things as group strength, fuel supply, fatigue or training.
Similarly, terrain is shown symbolically. Depicting terrain with topographic accuracy isn’t necessary and can actually become confusing, said Liana Suantak, a Ph.D. student who is working on the project with Rozenblit. Avenues of approach, choke points – such as mountain passes – and lines of defensible terrain don’t have to be represented with a high level of detail.
In addition to symbols that represent terrain and units, the simulation is said to use graphs to display other data. Instead of giving commanders columns of figures, the simulation displays bar graphs that show data at a glance, such as the relative strengths and weaknesses of units.
The result is reportedly a simulation that can be configured rapidly and run on a laptop computer. It gives a commander a compact, uncluttered depiction of the situation that’s simple and easily grasped, but rich in the information it provides.
The researchers couple this display with genetic algorithms to not only give battlefield commanders a clear view of the situation, but scenarios for addressing it.
To search every possible course of action would take a lot of time so the idea is to find a method that avoids unpromising strategies, Suantak said.
Genetic algorithms look at the ‘fitness function’ of possible solutions and highlight the most promising ones. By running through 50 or 100 generations, the genetic algorithms are designed to produce a strong solution in any given situation.
The symbolic visualisation software is well adapted to stability and support operations such as refugee relief, peace keeping and similar operations, such as supporting voting processes when establishing a new democratic government, Rozenblit said. ‘Traditionally, there has been no good way to represent situations in cities, where ethnic strife may be a problem. We can represent a lot of shades, where it is not really clear who the factions support and where the allegiances are shifting.’
The software has civilian applications, as well, particularly in disaster relief. ‘It can be used to represent situations where you need to evacuate people because of flooding, hurricanes or loss of power,’ Rozenblit said.
Rozenblit has been working on this symbolic visualisation software for about six years and now has a product that the US Army will be using for training and assessment.