3D path planning for unmanned aerial vehicles based on adaptive bald eagle search algorithm
An adaptive bald eagle search algorithm(ABES)is proposed and applied to the three-dimensional path planning problem of unmanned aerial vehicles(UAVs)to address the shortcomings of the bald eagle search algorithm(BES),which is prone to falling into local optima,low search efficiency,and low global search accuracy during optimization.In the selection stage of the algo-rithm,the parameters controlling the spiral trajectory are modified from fixed values to adaptive adjustments,thereby improving the algorithm's global exploration ability and convergence speed,and improving its performance.By creating a simulated three-dimensional geographic environment to simulate the flight conditions of unmanned aerial vehicles in real scenes,the ABES algorithm is used to solve path planning problems.Through comparative experiments,the excellent ability of the ABES algorithm in navigating various terrains and landforms was effectively tested.The experimental results demonstrate that the performance of the ABES algorithm has been improved,and it can quickly,stably,and effectively solve three-dimensional path planning problems.
bald eagle search algorithmadaptiveunmanned aerial vehicles3D path planningmetaheuristic algorithm
万方数据
维普
