Enhancing Lift and Dynamic Stability Through Morphological Optimization of Wings for Tailless Flapping-Wing Robots

The design of wings is crucial for tailless Flapping-wing robots (FWRs), as these robots rely exclusively on their wings for lift generation and body control. However, the current methodology for wing design primarily depends on the experience and heuristics of engineers. This study aims to explore the optimal wing shape design for our developed FWR, which has a height of 12 cm, a wingspan of 33 cm, and a weight of 30.8 g. The objectives are to maximize lift and enhance dynamic body stability. To achieve these goals, we first employ B-spline curves to parameterize the wings using a finite number of points. Additionally, we develop an analytical lift model based on the kinematics of the wings, taking the translational force, rotational force, and added mass force components into account. To improve the model's accuracy, a neural network is trained using experimental data of averaged lift. We also introduce constraints on wing design by considering the actuator's output power. Furthermore, an experimental setup is designed to assess the FWR's stability and its response to wind disturbances. Leveraging two global optimization algorithms, we obtain the optimal morphological parameters to enhance the lift and dynamic stability, respectively. A trade-off between maximum lift and maximum stability is observed. Ultimately, we achieve a 31.2% improvement in lift at the maximum actuator power output of the FWR with an improved payload from 3 grams to 10.6 grams, while another wing design can maintain better stability and controllability in windy environments.