A path planning method in three-dimensional complex space based on Bézier curves and a hybrid zebra optimization algorithm

For the safety and efficiency of aircraft executing tasks in complex environments, this paper presents a path planning method in three-dimensional space based on Bézier curve and a hybrid zebra optimization algorithm. Firstly, a path planning model using curves to directly generate flight paths is developed, by taking three kinds of flight costs as an objective function and control points as decision variables. To solve the established model with higher accuracy, a hybrid zebra optimization algorithm (HZOA) is constructed. It incorporates the hierarchical system of grey wolf optimization algorithm to form habitat searching strategy, which guides candidate solutions to approach better solutions by integrating information from the three pioneer zebras. Experimental results on CEC2019 test suite illustrate that the HZOA can get solutions with higher accuracy and faster convergence rate, especially in the late stage of searching. Meanwhile, its significantly superior performance to other comparison algorithms on more than half of all test functions is proved by the p values of the Kruskal–Wallis test. Finally, solving the path planning model through the HZOA, the results on three given simulated cases indicate paths obtained by HZOA have smaller total flight costs than those of other comparison algorithms for all simulated scenes. For the three sub-indicators, the approach based on HZOA ranks at least second to others, which proves it performs better in optimizing the flight distance, altitude and path smoothness.