Trajectory optimization algorithm based on B-spline curves

Trajectory optimization is one of the main focuses in the field of unmanned aerial vehicle path planning research. To improve the smoothness of the unmanned aerial vehicle’s planned trajectory and enhance its dynamic feasibility, trajectory optimization is performed using B-spline curves and flight constraints. This paper first applies B-spline curves to traditional path planning trajectories. Subsequently, the trajectory is re-optimized based on flight constraint equations and a time reallocation strategy. Finally, to validate the feasibility of the trajectory optimization algorithm, a simulation platform based on ROS was established for experimental verification. The experimental results indicate that the optimized unmanned aerial vehicle flight trajectory is smoother, maintains a safer distance from obstacles, and meets the dynamic feasibility requirements, thereby enhancing flight safety.