Population-Aware Sequential Flight Path Optimization for Low-Noise and Low-Fuel Consumption Departure Trajectory

Scalable enforcement of geometric non-interference constraints for gradient-based optimization

“…Additionally, it is desirable for the robot to maintain a safe distance from the anatomy, motivating the use of a distance-based non-interference constraint formulation in such problems. An example of an aerospace application is the representation of complex no-fly zone shapes in trajectory optimization (Kim and Liem 2022;Orndorff et al 2023).…”

“…We now apply our formulation to a number of geometric shapes involved in novel aircraft design. Aircraft design optimization is a long standing problem and has been the subject of recent interest in problems involving geometric non-interference constraints, e.g., the layout optimization of air cargo (Brandt 2017), trajectory optimization with complex no-fly zone shapes (Kim and Liem 2022;Orndorff et al 2023), aerodynamic shape optimization (Brelje et al 2020), and joint battery layout and wing shape optimization (Brelje 2021). To enable gradient-based design optimization involving these constraints, a new generic method is required to represent numerous components within an aircraft's design.…”

Noise- and Fuel-Minimal Departure Trajectory Optimization with Reinforcement Learning

“…One successful attempt is by decomposing the 4D trajectory optimization problem (3D in space + time) into lateral and vertical path planning in a work by Hartjes and Visser [13]. On top of that, Kim and Liem introduced non-preferable zones in additional to no-ŕy (i.e., restricted) zones by introducing a potential őeld [14]. The potential őeld represents relevant geographical data (e.g., population data), where higher repulsive potentials are assigned to non-preferable regions (e.g., high-population region that needs to be avoided by ŕight trajectories to reduce noise impact) to act as łpenaltyž of ŕying into these regions.…”