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The AutoSOAR autonomous soaring aircraft, part 1: Autonomy algorithms
Author(s) -
Depenbusch Nathan T.,
Bird John J.,
Langelaan Jack W.
Publication year - 2018
Publication title -
journal of field robotics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.152
H-Index - 96
eISSN - 1556-4967
pISSN - 1556-4959
DOI - 10.1002/rob.21782
Subject(s) - airspeed , exploit , lift (data mining) , computation , computer science , state (computer science) , range (aeronautics) , simulation , flight test , control engineering , engineering , aerospace engineering , algorithm , machine learning , computer security
Autonomous soaring has the potential to greatly improve both the range and endurance of small robotic aircraft. This paper describes an autonomous soaring system that generates a dynamic map of lift sources (thermals) in the environment and uses this map for online flight planning and decision making. 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 the aircraft behavior during flight and determines when changing behavior is appropriate. A complete system to enable autonomous soaring is described with special attention paid to practical considerations encountered during flight testing. A companion paper describes the hardware implementation of this system and the results of a flight test campaign conducted at Aberdeen Proving Ground in September 2015.