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Dynamic Mission Planning for Unmanned Aerial Vehicles

Rennu, Samantha R
http://orcid.org/0000-0002-4776-3000
http://rave.ohiolink.edu/etdc/view?acc_num=dayton16082274381124

Abstract Details

2020, Master of Science in Electrical Engineering, University of Dayton, Electrical and Computer Engineering.
The purpose of this thesis is to produce a closed-loop feedback mission planning tool that allows for the operator to control multiple Unmanned Aerial Vehicles (UAV) within a mission. Different styles of UAVs and mission planners that are available on the market were evaluated and selected for their cost, size, ability to customize, and fit for mission work. It was determined that commercially available mission planners do not provide the level of automation required, such as allowing for different algorithms for assigning UAV tasks and for planning UAV flight paths within a mission. Comparisons were made between different algorithms for path planning and tasking. From these comparisons, a bio-inspired machine-learning algorithm, Genetic Algorithm (GA), was chosen for assigning tasks to UAVs and Dubins path was chosen for modeling UAV flight paths within the mission simulation. Since market mission planners didn't allow for control of multiple UAVs, or wouldn't allow for the operator to add algorithms to increase usability and automation of the program, it was decided to create a Graphic User Interface (GUI) that would allow the operator to customize UAVs and the mission scenario. A test mission scenario was then designed, which included 9 Points of Interest (POI), 1 to 3 Targets of Interest (TOI), 3 to 5 UAVs, as well as simulation options that modeled failure of a task or a UAV crash. Operator feedback was incorporated into the simulation by allowing the operator to determine a course of action if a failure occurred, such as reprogramming the other UAVs to complete the tasks left by the crashed UAV or reassessing a failed task. Overall mission times decreased for reprogramming the UAVs versus running a separate mission to complete any tasks left by the crashed UAV. Additional code was added to the GA and Dubins path to increase speed without decreasing solution fitness.
Amy Neidhard-Doll, Ph.D. (Advisor)
Eric Balster, Ph.D. (Committee Member)
Bradley Ratliff, Ph.D. (Committee Member)
83 p.
Electrical Engineering
UAV; Genetic Algorithm; Dubins Path; Mission Planner; GUI; Dynamic Planning; Closed-Loop Feedback; Unmanned Aerial Vehicles; Interactive Simulation; MATLAB; GUIDE; Flight Path Planning; Task Planning

Recommended Citations

Citations

  • Rennu, S. R. (2020). Dynamic Mission Planning for Unmanned Aerial Vehicles [Master's thesis, University of Dayton]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=dayton16082274381124

    APA Style (7th edition)

  • Rennu, Samantha. Dynamic Mission Planning for Unmanned Aerial Vehicles. 2020. University of Dayton, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=dayton16082274381124.

    MLA Style (8th edition)

  • Rennu, Samantha. "Dynamic Mission Planning for Unmanned Aerial Vehicles." Master's thesis, University of Dayton, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=dayton16082274381124

    Chicago Manual of Style (17th edition)

dayton16082274381124
325
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This open access ETD is published by University of Dayton and OhioLINK.