Algorithms, Implementation, and Flight Test Results of the AutoSOAR Platform
Autonomous soaring has the potential to greatly improve both the range and endurance of small uninhabited aerial vehicles. This presentation will describe the results of a test
flight campaign that demonstrated an autonomous soaring system that generates a
dynamic map of lift sources (thermals) in the environment and used 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 hours flight time with
the autonomous soaring system engaged, with three hours spent climbing in thermals.
The presentation will also discuss observations of soaring birds: vulture and bald eagles
were active during the test flights, and often flew in close proximity to the AutoSOAR
Jack Langelaan is an Associate Professor in the Department of Aerospace Engineering at Penn State University. His research focuses on path planning, control, state estimation and data fusion, applied especially to navigation, obstacle avoidance, and long-range flight of small uninhabited aircraft. He received his Ph.D. in Aeronautics and Astronautics from Stanford University in 2006; prior to Stanford he worked as an engineer at Bombardier Aerospace in Toronto, Canada.