Author Information

Courtney ThurstonFollow

Is this project an undergraduate, graduate, or faculty project?

Undergraduate

individual

Authors' Class Standing

Courtney Thurston, Junior

Lead Presenter's Name

Courtney Thurston

Faculty Mentor Name

Dr. Richard Stansbury

Abstract

Constraint-satisfaction programming is a method that can be applied to choose appropriate flight path segments for the operation of unmanned aerial systems, maximizing the safety of their flight path while remaining agile and able to avoid obstacles throughout navigation. CSPs provide a framework in which multiple conflicting constraints (such as no-fly zones found over airports, military bases, et cetera) imposed upon the unmanned system can be resolved in such a way that the unmanned system will not only perform correctly, but also will meet or exceed its performance expectations. Constraints also provide an agile way to allow the system to change directions depending on unforeseen circumstances such as obstacles (tall buildings, etc), avoiding the problem of not being able to re-route, which occurs when you use hard-coded routes. By incorporating performance objectives into the our constraint model, the research project result is capable of rationally guiding UAS through a flight path that best meets its current needs and goals. An unmanned system must select tasks, such as certain flight segments and the overall route requirement (must get from point A to point B), and configure them accordingly within its hardware and software to truly be autonomous. A task is any unmanned systemic action or series of actions to achieve some state or goal. These set of tasks to choose from may be derived from a variety of sources; the tasks could stem from a queue of requests from users or companies.

Did this research project receive funding support (Spark or Ignite Grants) from the Office of Undergraduate Research?

Yes, Ignite Grant

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Constraint programming mapping and evaluation techniques applied to critical unmanned aerial system decision-making

Constraint-satisfaction programming is a method that can be applied to choose appropriate flight path segments for the operation of unmanned aerial systems, maximizing the safety of their flight path while remaining agile and able to avoid obstacles throughout navigation. CSPs provide a framework in which multiple conflicting constraints (such as no-fly zones found over airports, military bases, et cetera) imposed upon the unmanned system can be resolved in such a way that the unmanned system will not only perform correctly, but also will meet or exceed its performance expectations. Constraints also provide an agile way to allow the system to change directions depending on unforeseen circumstances such as obstacles (tall buildings, etc), avoiding the problem of not being able to re-route, which occurs when you use hard-coded routes. By incorporating performance objectives into the our constraint model, the research project result is capable of rationally guiding UAS through a flight path that best meets its current needs and goals. An unmanned system must select tasks, such as certain flight segments and the overall route requirement (must get from point A to point B), and configure them accordingly within its hardware and software to truly be autonomous. A task is any unmanned systemic action or series of actions to achieve some state or goal. These set of tasks to choose from may be derived from a variety of sources; the tasks could stem from a queue of requests from users or companies.

 

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