Autonomous soaring has the potential to greatly improve both the range and endurance of small robotic aircraft. This paper describes the results of a test flight campaign to demonstrate an autonomous soaring system that generates a dynamic map of lift sources (thermals) in the environment and uses this map for on-line flight planning and decision making. The aircraft is based on a commercially available radio-controlled glider; it is equipped with an autopilot module for low-level flight control and on-board computer that hosts all autonomy algorithms. Components of the autonomy algorithm include thermal mapping, explore/exploit decision making, navigation, optimal airspeed computation, thermal centering control, and energy state estimation. A finite state machine manages flight behaviors and switching between behaviors. Flight tests at Aberdeen Proving Ground resulted in 7.8 h flight time with the autonomous soaring system engaged, with three hours spent climbing in thermals. Postflight computation of energy state and frequent observations of groups of birds thermalling with our aircraft indicate that it was effectively exploiting available energy.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications