Autonomous Airborne Sensor Management under Dynamic and Uncertain Environments.

With a high demand of the ever-increasing level of automation, defence is moving towards goal-oriented operation. This entails the specification of what the system needs to achieve at a high level. In order to achieve this, a Goal-Oriented Control System is essential. This project will investigate a system that is able to receive high level mission goals and produce scheduled micro-scale tasks for sensors onboard an airborne platform, in real-time dynamic environments. This creates four research areas:

Goal Decomposition - the GOCS system will be required to perform thorough and accurate decomposition of the desired high-level goals. This decomposition should simultaneously perform an initial 'sub-optimization' in order to gain the necessary steps to achieve the task.
Optimization - The decomposed tasks should be fully optimized for both the environmental situation, the mission constraints and the desired goals. The aim of the optimization should be to maximise the success of the mission, whether it is surveillance of a specified area, loitering efficiently or travelling from A to B. It should also be able to communicate with the higher-level mission manager to request changes to the mission plan in order to achieve a better percentage of success.
Feasibility - Whilst the optimal outcome is desired for every mission, it would not be sensible to attempt to achieve this as there will be limits both physically and computationally. For this reason, the optimization should be fully aware of the available resources and produce an output that is foremost achievable. Where a command cannot be met due to limits on the system capability, the system should communicate back to the mission manager with a percentage of possible achievement of the goal in the current situation.
Adaptability - The operating environment could be highly unpredictable. This means the GOCS should be able to rapidly adapt to changes in the situation in order to maintain the highest possible success of the mission. This could mean large divergence from the initial output.