Scalable Online Flight Trajectory Optimization via Sequential Quadratic Programming for Urban Air Mobility in Ultra Low-Altitude Airspace
2026-06-22 • Emerging Technologies
Emerging Technologies
AI summaryⓘ
The authors developed a way for flying vehicles in cities to plan safe paths that avoid crashes, even among many tall buildings. Instead of mapping out safe zones beforehand, their method checks for obstacles and adjusts paths continuously as the vehicle moves. They use a mathematical approach called Sequential Quadratic Programming that handles vehicle behavior and city shapes together in real time, which works at the scale of entire cities. Tests showed their method always found safe, clear paths using only standard computer power.
Urban Air MobilitySequential Quadratic ProgrammingTrajectory OptimizationObstacle AvoidanceQuadtree DecompositionVehicle DynamicsReal-time PlanningCollision-free Trajectories3D Environment MappingDifferential Dynamic Programming
Authors
Josue N. Rivera, Bohang Liang, Chen Lv, James Wang
Abstract
As Urban Air Mobility (UAM) scales toward high-density operations, generating collision-free trajectories within complex 3D cityscapes is a critical safety requirement. This paper proposes a scalable Sequential Quadratic Programming (SQP) framework that integrates geometric environmental constraints, operational limits, and vehicle dynamics within a single online trajectory optimization process. Rather than precomputing obstacle-free corridors ahead of time, our method encodes obstacle avoidance as live separating-hyperplane constraints regenerated at every solver iteration, so that dense urban geometry and full-DOF vehicle dynamics are resolved jointly and online as the reference and environment evolve. A variable-scale quadtree decomposition keeps computation bounded, enabling the framework to scale to city-wide environments while preserving real-time performance for high-speed flight. We validate the framework against conventional SQP, Iterative Linear Quadratic Regulator, and Differential Dynamic Programming across flights in five real-world urban centers, attaining 100% success and clearance rates on CPU-only hardware.