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Title:Flight maneuver automation for system analysis of small fixed-wing UAVs
Author(s):Yu, Simon
Contributor(s):Caccamo, Marco
Subject(s):Unmanned Aerial Vehicle (UAV)
Flight Testing
Flight Control
Mission Planning
Software Engineering
Abstract:The application of Unmanned Aerial Vehicles (UAVs) has become increasingly versatile, creating new opportunities in the diverse fields of technology and business. However, this increase in variety also results in progressively challenging and complex flight maneuver sequences for UAVs to perform. In order to simplify such a process, this work presents a software framework that automates and streamlines the sequential executions of independent flight maneuvers. The flight maneuver automation framework consists of several software modules, ranging from maneuver planning, condition managing, and flight analysis, to graphical user interface (GUI) and user configurations. Traditional global planning in an aircraft autopilot framework provides simple, position-based trajectory planning. A typical unmanned mission consists of position trajectories generated from several way-points. When executed, the position-based definition of the pre-generated paths limits the capabilities of the UAVs. Thus, this work describes an automated flight maneuver planning which provides a robust, condition-based framework that augments the conventional mission planning. Instead of generating fixed paths from position way-points, the automated framework creates autonomous maneuvers in terms of any states of the aircraft, such as position, velocity, attitude, and so on, and sequentially transitions to the next maneuver based on the states of the aircraft. The flight maneuver automation framework is implemented in the modular uavAP autopilot deployed on a fixed-wing UAV test-bed and validated using the real-time uavEE emulation environment. Finally, this work describes the application of the flight maneuver framework for automating flight testing processes and streamlining system identification and analysis for small UAVs. In addition, the framework also provides a platform for the implementation and the validation for a robust kinematic model and an advanced geofencing algorithm for fixed-wing aircraft that tackle the primary concern of keeping the UAVs inside a designated geofencing region.
Issue Date:2019-05
Sponsor:work supported by the National Science Foundation (NSF) under grant number CNS-1646383
Date Available in IDEALS:2019-06-19

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