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UAV Traffic Management for National Airspace Integration

Radmanesh, Mohammadreza
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1461593199

Abstract Details

2016, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
This thesis focuses on developing optimization algorithms for path planning of single and cooperating Unmanned Air Vehicles (UAVs), operating in National Air Space (NAS), in presence of other moving and/or stationary obstacles. The problem is formulated in the framework of Mixed Integer Linear Programming (MILP) which has been proven to be efficient in literature for solving optimization problems in other domains well as path planning problems. This thesis extends the works carried out in literature via proposing the cost-to-go function that incorporates a number of criteria such as path length, uncertain nature of NAS environment, and time and energy consumption based on detailed dynamical model of motion in three dimensions taking into consideration various UAV constraints. The problem is first formulated using single vehicle and then extended to multiple vehicles having a common goal which is incorporated using motion constraints. The solution of the MILP is based on a fast Floating Point (FP) method and is provided in detail in this thesis. This method results in decrease of the computational effort. Incorporation of the moving obstacles or Intruder Aircrafts (IAs) in the problem is done using Kalman filter and Bayesian framework that enable us to simulate uncertainty in motion of obstacles (or intruder aircraft) and maintain the distance between the UAV fleet and other non-cooperative airplanes in NAS. In result, this approach enables simulation of vehicles in team while guaranteeing the robust fleet in uncertain domain. Bayesian method helps us to overcome the hindrance of implementing this algorithm in dynamic and uncertain environment including IAs and pop-up threats. The proposed methodology for solving cooperative form of centralized control in the framework of MILP for cooperative UAVs is shown to result in robust solutions and improves overall team performance. All the algorithms are tested and demonstrated via a number of numerical studies. The results indicate that the proposed algorithms are successful in obtaining optimal solutions in a computationally efficient manner that can be applied to online path planning in dynamic and uncertain situations.
Manish Kumar, Ph.D. (Committee Chair)
Kelly Cohen, Ph.D. (Committee Member)
Ali Minai, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
118 p.
Engineering
National Air Space; Mixed Integer Linear Programming; Obstacle Avoidance; Trajectory Planning; UAV; Optimization

Recommended Citations

Citations

  • Radmanesh, M. (2016). UAV Traffic Management for National Airspace Integration [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1461593199

    APA Style (7th edition)

  • Radmanesh, Mohammadreza. UAV Traffic Management for National Airspace Integration. 2016. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1461593199.

    MLA Style (8th edition)

  • Radmanesh, Mohammadreza. "UAV Traffic Management for National Airspace Integration." Master's thesis, University of Cincinnati, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1461593199

    Chicago Manual of Style (17th edition)

ucin1461593199
714
© 2016, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.