Trajectory Optimization for Helicopter Unmanned Aerial Vehicles (UAVs)

Abstract

This thesis explores the numerical methods and software development for optimal trajectories of a specific model of Helicopter Unmanned Aerial Vehicle (UAV) in an obstacle-rich environment. This particular model is adopted from the UAV Laboratory of the National University of Singapore who built and simulated flights for an X-Cell 60 small-scale UAV Helicopter. The code, which allowed the team to simulate flights, is a complex system of non-linear differential equations-15 state variables and four control variables-used to maneuver the state trajectories. This non-linear model is incorporated into a separate optimization algorithm code, which allows the user to set initial and final time conditions together with various constraints, and, using the same variable scheme, optimize a trajectory. The optimal trajectory is defined by using a cost function-the performance measure-and the system is subject to a set of constraints (such as mechanical limitations and physical three-dimensional obstacles). Simulations conclude that solutions are readily obtained; however, it is still very difficult to derive trajectories that are truly optimal, and our work calls for more future research in computational programs for optimal trajectory planning. All simulations in this thesis are modeled using the MATLAB program.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2010
Accession Number
ADA524550

Entities

People

  • Benjamin T. Gatzke

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Space

DTIC Thesaurus Topics

  • Aircrafts
  • Algorithms
  • Applied Mathematics
  • Collision Avoidance
  • Computational Science
  • Control Systems
  • Differential Equations
  • Geometry
  • Helicopters
  • Mathematics
  • Nonlinear Dynamics
  • Rotary Wing Aircraft
  • Simulations
  • Three Dimensional
  • United States
  • United States Military Academy
  • Unmanned Aerial Vehicles

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aviation Science / Aeronautics.
  • Computational Modeling and Simulation

Technology Areas

  • Autonomy