Study on the Glider Soaring Strategy in Random Location Thermal Updraft via Reinforcement Learning

Abstract

Soaring birds can use thermal updrafts in natural environments to fly for long periods or distances. The flight strategy of soaring birds can be implemented to gliders to increase their flight time. Currently, studies on soaring flight strategies focus on the turbulent nature of updrafts while neglecting the random characteristics of its generation and disappearance. In addition, most flight strategies only focus on utilizing updrafts while neglecting how to explore it. Therefore, in this paper, a complete flight strategy that seeks and uses random location thermal updrafts is mainly emphasized and developed. Moreover, through the derivation of flight dynamics and related formulas, the principle of gliders acquiring energy from thermal updrafts is explained through energy concepts. This concept lays a theoretical foundation for research on soaring flight strategies. Furthermore, the method of reinforcement learning is adopted, and a perception strategy suitable for gliders that considers the vertical ground speed, vertical ground speed change rate, heading angle, and heading angle change as the main perception factors is developed. Meanwhile, an area exploring strategy was trained by reinforcement learning, and the two strategies were combined into a complete flight strategy that seeks and uses updrafts. Finally, based on the guidance of the soaring strategy, the flight of the glider in the simulation environment is tested. The soaring strategy is verified to significantly improve the flight time lengths of gliders.