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A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance

Authors
  • Goerzen, C.1
  • Kong, Z.2
  • Mettler, B.2
  • 1 San Jose State University Research Foundation, NASA Ames Research Center, Moffett Field, CA, 94035, USA , Moffett Field (United States)
  • 2 University of Minnesota, Department of Aerospace Engineering and Mechanics, Minneapolis, USA , Minneapolis (United States)
Type
Published Article
Journal
Journal of Intelligent & Robotic Systems
Publisher
Springer-Verlag
Publication Date
Nov 17, 2009
Volume
57
Issue
1-4
Identifiers
DOI: 10.1007/s10846-009-9383-1
Source
Springer Nature
Keywords
License
Yellow

Abstract

A fundamental aspect of autonomous vehicle guidance is planning trajectories. Historically, two fields have contributed to trajectory or motion planning methods: robotics and dynamics and control. The former typically have a stronger focus on computational issues and real-time robot control, while the latter emphasize the dynamic behavior and more specific aspects of trajectory performance. Guidance for Unmanned Aerial Vehicles (UAVs), including fixed- and rotary-wing aircraft, involves significant differences from most traditionally defined mobile and manipulator robots. Qualities characteristic to UAVs include non-trivial dynamics, three-dimensional environments, disturbed operating conditions, and high levels of uncertainty in state knowledge. Otherwise, UAV guidance shares qualities with typical robotic motion planning problems, including partial knowledge of the environment and tasks that can range from basic goal interception, which can be precisely specified, to more general tasks like surveillance and reconnaissance, which are harder to specify. These basic planning problems involve continual interaction with the environment. The purpose of this paper is to provide an overview of existing motion planning algorithms while adding perspectives and practical examples from UAV guidance approaches.

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