A Novel GEA–PSO Method for Optimizing the Parameters of a Bird-Like Flapping Wing Robot
Abstract
A novel parameter optimization method, named the geyser algorithm based on particle swarm optimization (GEA–PSO) method, was proposed for optimizing the key parameters of a bird-like flapping wing robot. The kinematic model, the multiple objective functions, and some constraint conditions were first established. A novel GEA–PSO algorithm was designed. Some test functions verified the good superiority of the GEA–PSO method with a fast velocity and high accuracy. The key parameters of the robot were successfully optimized using the GEA–PSO method. Kinematic simulations were carried out to obtain some key quantities, such as the end trajectory, the flapping angle, and the folding angle. Robot experiments were conducted based on the robot prototype, which verified the effectiveness of the optimization method. The GEA–PSO method plays a crucial role in the parameter optimizations and the stable flights of the robot.
