Designing quiet rotorcraft landing trajectories with probabilistic road maps.

Next generation commercial air transportation will likely see an increased use of rotorcraft, including helicopter and tilt-rotors. Two advantages of rotorcraft with respect to fixed wing aircraft are the optimized aerodynamic levitation and the possibility of takeoff and landing without a runway, which minimizes their interference with fixed wing traffic. A recurring obstacle to rotorcraft integration is the ground noise they generate, particularly near residential areas and hospitals. The problem of rotorcraft ground noise can be partially addressed by designing new flight profiles, in particular landing trajectories, that have a lower impact in the noise produced by a rotorcraft. In this paper we approach this problem computationally by modeling a high dimensional environment able to capture many parameters of landing trajectories that contribute to ground noise, and using probabilistic road maps (PRMs), coupled with a robust ground noise simulation system, for identifying noise-minimal approach trajectories.