Co-Evolving Mission Planner (CEMP). Initially we worked on a short (three month) project to demonstrate the feasibility of using distributed multi-objective optimisers to generate coordinated mission plans for small teams of unmanned aerial vehicles (UAVs).
Using an evolutionary algorithm-based, multi-objective optimisation technique, we considered mission planning factors such as area of search area coverage, restricted airspace constraints, maximum ground control station range, adverse weather effects, airspace collision avoidance, energy minimisation, path linearity, named area of analysis emphasis, and sensor performance.
This algorithm development work aligns with the ‘Multi-task, multi-asset planning & allocation’ topic within the GAMMA programme.
Expert knowledge for the algorithm was provided by The Great Circle, with software development support and underpinning optimisation techniques coming from both the University of Central Lancashire (UCLan) and The Great Circle.
Further work was then carried out to mature the applications in order to demonstrate them in a synthetic environment. This resulted in a demonstration at the Virtual Engineering Centre (Daresbury Science Park) where we successfully flew 4 UAVs with a complex set of mission objectives over Silverstone Race Track.