Small Unmanned Aircraft

By R. Beard, Timothy W. McLain. 2012

1,363 citations recorded by the source corpus.

Autonomous unmanned air vehicles (UAVs) are critical to current and future military, civil, and commercial operations. Despite their importance, no previous textbook has accessibly introduced UAVs to students in the engineering, computer, and science disciplines--until now. Small Unmanned Aircraft provides a concise but comprehensive description of the key concepts and technologies underlying the dynamics, control, and guidance of fixed-wing unmanned aircraft, and enables all students with an introductory-level background in controls or robotics to enter this exciting and important area. The authors explore the essential underlying physics and sensors of UAV problems, including low-level autopilot for stability and higher-level autopilot functions of path planning. The textbook leads the student from rigid-body dynamics through aerodynamics, stability augmentation, and state estimation using onboard sensors, to maneuvering through obstacles. To facilitate understanding, the authors have replaced traditional homework assignments with a simulation project using the MATLAB/Simulink environment. Students begin by modeling rigid-body dynamics, then add aerodynamics and sensor models. They develop low-level autopilot code, extended Kalman filters for state estimation, path-following routines, and high-level path-planning algorithms. The final chapter of the book focuses on UAV guidance using machine vision. Designed for advanced undergraduate or graduate students in engineering or the sciences, this book offers a bridge to the aerodynamics and control of UAV flight.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/955ec4678be44cdb5c00ecad136866d7bd77ea25

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

  1. Walid Saad
  2. Medhi Bennis
  3. Merouane Debbah
  4. Mohammad Mozaffari
  5. Young-Han Nam
  6. Rui Zhang
  7. Timothy W. McLain
  8. Yong Zeng

In Computer Vision and Pattern Recognition

  1. R. Beard
  2. Robert C. Leishman
  3. Jeff Ferrin
  4. Timothy W. McLain
  5. Merouane Debbah
  6. Walid Saad
  7. Medhi Bennis
  8. Mohammad Mozaffari

Citations in the corpus