3D Path Planning and Tracking of Quadrotors Based on Improved Whale Optimization Algorithm

Aiming at the shortcomings of standard whale optimization algorithm (WOA) in three-dimensional (3D) path planning of quadrotors, such as long path length, high time-consumption and path roughness, an improved whale optimization algorithm called SAMWOA is proposed in this paper. Firstly, Singer chaotic mapping strategy is introduced to enrich the diversity of whale population and improve the quality of initial solution of the algorithm. Secondly, an adaptive cognitive factor is proposed to improve the position updating method of the whale leader and balance the exploration and development ability. Then, the wavelet mutation mechanism is used to disturb the current optimal solution position of the whale population, so that the algorithm can jump out of the local optimum. Moreover, the cubic spline interpolation method is utilized to smooth the path planned by the proposed SAMWOA. Finally, the proposed SAMWOA is applied to the 3D path planning and tracking of the quadrotor. The simulation results show that, compared with the WOA, the path length, steering cost and time-consuming planned by the proposed SAMWOA is reduced by 25.78%, 37.5% and 42.21%, respectively. The proposed SAMWOA not only solves the issues of the WOA, but also can plan and track the 3D path and avoid obstacles in real time, which is advanced and robust.