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.
|Original language||English (US)|
|Number of pages||36|
|Journal||Journal of Intelligent and Robotic Systems: Theory and Applications|
|State||Published - Jan 2010|
Bibliographical noteFunding Information:
Acknowledgements This work owes its existence to the funding from the Army Aeroflightdynam-ics Directorate, and collaboration with the ongoing Autonomous Rotorcraft Project.
This research was completed under grants NNX08A134A (San Jose State University Research Foundation) and NNX07AN31A (University of Minnesota) as part of the US Army Aeroflightdynamics Directorate (RDECOM) flight control program.
- Motion planning