UAS mission path planning system (MPPS) using hybrid-game coupled to multi-objective optimiser - testing - this is updated
DongSeop Lee, Jacques Périaux, Felipé Gonzalez, Mark Harrison · 2009
This paper presents the application of advanced optimization techniques to unmannedaerial system mission path planning system (MPPS) using multi-objective evolutionaryalgorithms (MOEAs). Two types of multi-objective optimizers are compared; the MOEAnondominated sorting genetic algorithm II and a hybrid-game strategy are implementedto produce a set of optimal collision-free trajectories in a three-dimensional environment.The resulting trajectories on a three-dimensional terrain are collision-free and are representedby using Bezier spline curves from start position to target and then target to startposition or different positions with altitude constraints. The efficiency of the two optimizationmethods is compared in terms of computational cost and design quality. Numericalresults show the benefits of adding a hybrid-game strategy to a MOEA and for aMPPS. this is updated