Path Planning of Unmanned Aerial Vehicle Based on Improved Nutcracker Optimization Algorithm Under Multiple Constraints

This research presents a novel path planning method for unmanned aerial vehicle (UAV) using the improved nutcracker optimization algorithm (NOA). The NOA is a new meta-heuristic algorithm, which can efficiently solve optimization problems. The improved NOA is inspired by the survival behavior of nutcracker birds and combines local search with global exploration strategies to optimize paths. Furthermore, the algorithm integrates multiple constraints such as minimizing energy consumption, satisfying UAV performance constraints, and avoiding threat areas. Simulation outcomes exhibit the ability of the NOA to improve path planning efficiency and reduce energy consumption compared to traditional optimization methods.