Fuzzy multi-objective mission flight planning in unmanned aerial systems

This paper discusses the development of a multiobjective\ud mission flight planning algorithm for Unmanned\ud Aerial System (UAS) operations within the National Airspace\ud System (NAS). Existing methods for multi-objective planning\ud are largely confined to two dimensional searches and/or acyclic\ud graphs in deterministic environments; many are\ud computationally infeasible for large state spaces. In this paper,\ud a multi-objective fuzzy logic decision maker is used to augment\ud the D* Lite graph search algorithm in finding a near optimal\ud path. This not only enables evaluation and trade-off between\ud multiple objectives when choosing a path in three dimensional\ud space, but also allows for the modelling of data uncertainty. A\ud case study scenario is developed to illustrate the performance of\ud a number of different algorithms. It is shown that a fuzzy multiobjective\ud mission flight planner provides a viable method for\ud embedding human expert knowledge in a computationally\ud feasible algorithm