Aircraft Path Planning in Stochastic Wind Environments: Algorithms, Implementation, and Benchmarking Protocols

This technical report documents the design, mathematical formulation, implementation, and validation of two aircraft path planning frameworks developed for three-dimensional environments subject to synthetic stochastic wind disturbances. The first framework is a statistically rigorous benchmark of three path planning architectures: GART (Guiding Attraction-based Random Tree), RRT* (Rapidly-exploring Random Tree Star), and Hybrid PRM-RRT* (Probabilistic Roadmap combined with RRT* local refinement). The second framework is STRIVE-VNS (Strategic Trajectory Refinement and Instability Validation Engine, Variable Neighborhood Search), a multi-strategy planner that coordinates thirteen heterogeneous sampling-based planners within a VNS optimization architecture. Both frameworks share a common simulation environment, cost function family, wind field model, kinematic constraint model, and statistical evaluation protocol, making them complementary studies of path planning under identical environmental assumptions. The report covers the full software implementation in MATLAB R2023a, including every algorithm, scenario configuration, wind field generator, statistical test, and random seed required to reproduce all results reported in the associated journal articles. The implementation is structured so that either framework can be run independently or the two can be executed in sequence as a progressive evaluation pipeline. This report is deposited alongside the companion MATLAB implementation and is intended to be read together with the associated PhD thesis on fault-tolerant nonlinear control for thrust-vectored aircraft. The path planning work reported here addresses the trajectory generation component of the broader flight safety problem treated in the thesis.