Experimental Assessment of Online Dynamic Soaring Optimization for Small Unmanned Aircraft

Small unmanned aircraft systems (sUAS) have been responsible for launching a rapidly growing industry that aims to perform sensing or surveillance tasks that are regarded as dangerous or expensive for humans. Industrial applications for fixed-wing platforms include agricultural crop management, high-frequency aerial photography, and persistent weather observation, to name a few. With the complexity of these systems considered, industry has regarded sUAS platforms as ”sensors in the sky” that can provide real-time information about our environment. Fixed-wing sUAS can carry an advantage over quadrotor systems with longer endurance, increased range, and higher cruise velocity. In relatively open skies, these benefits enable greater mission coverage area with an ability to perform greater duration persistent sensing missions. However most sUAS are power-limited by the on-board battery for aircraft performance. Greater sUAS endurance is needed to make several conceptual applications feasible. Attempts to address sUAS relatively short endurance have been made, particularly within the military sphere. Refueling autonomous sUAS with another aircraft has proven to be a challenging task whose complexity often exceeds practicality and is not applicable to electric motor aircraft. Laser-based systems have been proposed and tested in which a high-power beam is focused on a photovoltaic array attached to the underside of an sUAS. These systems are not only costly, but also ineffective in long-range applications or inclement weather that would obstruct direct line-of-sight. These strategies’ drawbacks stem from generating power on the ground and then attempting to transfer it to the vehicle while in flight. Soaring is a flight technique that extracts wind energy from the immediate surrounding environment and converts it to aircraft potential (Figure 1). Wind is an abundant source of kinetic energy in the atmosphere that can be effectively harnessed given sufficient knowledge of the environment. Soaring exploits the wind by gaining potential energy from wind or thermals and spends this potential to stay aloft. Based on the wind direction, magnitude, and gradient the sUAS executes maneuvers to ensure aircraft sink rate is less than the climb provided by the wind. Developing optimized dynamic soaring trajectories is a well-researched topic and has led to several proposals for harnessing wind energy to improve sUAS performance. However, the majority of existing work fails to address the implementation of such a trajectory optimization layer for use in field testing to evaluate performance in a non-simulated environment. Developing a flight system architecture that incorporates online planning and control algorithms poses several practical software and hardware implementation challenges. Such a system must be robust to changing environmental conditions, must be adaptable for unexpected communication interruptions, and adapt to several mission profiles. Related works have investigated using optimization to develop soaring trajectories. These works examine the theoretical problem formulation for nonlinear optimization problems by evaluating different cost functions that aim to increase flight endurance. Most works evaluate trajectories by comparing them to a baseline Monte Carlo simulation. Some approaches demonstrated successfully within a hardware in the loop (HIL) environment, however, a simulated shear ridge is assumed for the wind simulations and all the trajectories are computed in advance. While this requires less online computation, the available library of trajectories may not contain a suitable match for the current wind conditions during flight.