Wind-Aware Energy-Efficient Trajectory Planning for Flapping-Wing Robots

Flapping-wing robots have recently attracted significant interest due to their agility and potential energy efficiency compared to traditional aerial systems such as multirotor vehicles. Inspired by bird flight, these novel aerial robots generate thrust and a portion of their lift through wing flapping, while also maintaining lift passively even when the wings are not actively flapping. These robots can switch between the flapping and gliding modes, enabling energy-efficient navigation strategies. However, the design of optimal navigation trajectories that consider the effect of the wind remains unexplored. This paper presents a novel approach to flapping-wing aerial navigation that leverages wind conditions to reduce energy consumption during flight. A physics-based trajectory optimization framework that adjusts the control inputs (flapping frequency and elevator) is formulated based on a dynamic model of the flapping-wing robot, including wind effects. Through optimization-based trajectory planning, our proposed solution adjusts the robot’s flight to take advantage of favorable wind patterns, thereby reducing energy consumption. Our results demonstrate significant energy savings, validating the potential of wind-aware strategies to improve the endurance and efficiency of flapping-wing aerial vehicles.