UAV Path Planning with A-STAR Algorithm and Path Smoothing Implementation

UAV path planning refers to a technology designed to enable unmanned aerial vehicles to follow specific flight routes for accomplishing various missions. The A-STAR algorithm serves as a widely adopted path planning method that achieves autonomous UAV navigation by searching for the shortest path on a map through heuristic evaluation functions. In code implementation, the A-STAR algorithm typically utilizes open and closed lists with cost functions (f = g + h) where g represents the actual cost from the start node and h denotes the heuristic estimate to the goal. For path smoothing optimization, algorithms like B-spline curves are employed to refine UAV flight trajectories by generating continuous curvature paths that avoid sharp turns. These techniques significantly enhance UAV flight efficiency and precision, enabling operation in complex environments through computationally efficient route planning and smooth trajectory execution. The implementation typically involves waypoint interpolation using mathematical spline functions that maintain derivative continuity while satisfying boundary constraints.