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Selected papers from the 2nd International Symposium on UAVs, Reno, U.S.A. June 8-10, 2009

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  • © 2010


  • Publishes the latest research findings, not published anywhere else
  • Presents current status of unmanned aviation
  • Discusses levels of autonomy and sensor-based navigation
  • Includes real case studies

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Table of contents (26 chapters)


About this book

In the last decade, signi?cant changes have occurred in the ?eld of vehicle motion planning, and for UAVs in particular. UAV motion planning is especially dif?cult due to several complexities not considered by earlier planning strategies: the - creased importance of differential constraints, atmospheric turbulence which makes it impossible to follow a pre-computed plan precisely, uncertainty in the vehicle state, and limited knowledge about the environment due to limited sensor capabilities. These differences have motivated the increased use of feedback and other control engineering techniques for motion planning. The lack of exact algorithms for these problems and dif?culty inherent in characterizing approximation algorithms makes it impractical to determine algorithm time complexity, completeness, and even soundness. This gap has not yet been addressed by statistical characterization of experimental performance of algorithms and benchmarking. Because of this overall lack of knowledge, it is dif?cult to design a guidance system, let alone choose the algorithm. Throughout this paper we keep in mind some of the general characteristics and requirements pertaining to UAVs. A UAV is typically modeled as having velocity and acceleration constraints (and potentially the higher-order differential constraints associated with the equations of motion), and the objective is to guide the vehicle towards a goal through an obstacle ?eld. A UAV guidance problem is typically characterized by a three-dimensional problem space, limited information about the environment, on-board sensors with limited range, speed and acceleration constraints, and uncertainty in vehicle state and sensor data.

Editors and Affiliations

  • Department of Electrical and Computer Engineering, CMK 300 School of Engineering and Computer Science, University of Denver, Denver, USA

    Kimon P. Valavanis

  • Dept. Electrical & Computer Engineering, Brigham Young University, Provo, USA

    Randal Beard

  • Applied Engineering Technology Program, Drexel University, Philadelphia, USA

    Paul Oh

  • Depto. Ingeniera Sistemas y Automática Camino de los Descubrimientos, Universidad de Sevilla Escuela Superior de Ingenieros, Sevilla, Spain

    Aníbal Ollero

  • Dept. Computer Science & Engineering, University of South Florida, Tampa, USA

    Leslie A. Piegl

  • Korea Advanced Institute of Science & Technology (KAIST), Department of Aerospace Engineering, Republic of South Korea

    Hyunchui Shim

Bibliographic Information

  • Book Title: Selected papers from the 2nd International Symposium on UAVs, Reno, U.S.A. June 8-10, 2009

  • Editors: Kimon P. Valavanis, Randal Beard, Paul Oh, Aníbal Ollero, Leslie A. Piegl, Hyunchui Shim

  • DOI:

  • Publisher: Springer Dordrecht

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer Science+Business Media B.V. 2010

  • Hardcover ISBN: 978-90-481-8763-8Published: 15 March 2010

  • Softcover ISBN: 978-94-007-9158-9Published: 06 November 2014

  • eBook ISBN: 978-90-481-8764-5Published: 11 April 2011

  • Edition Number: 1

  • Number of Pages: VI, 529

  • Additional Information: Reprinted from JOURNAL OF INTELLIGENT AND ROBOTIC SYSTEMS, 57:1-4, 2010

  • Topics: Control and Systems Theory, Engineering Design, Electrical Engineering, Control, Robotics, Mechatronics, Systems Theory, Control

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