Maneuver-based autonomous navigation of a small fixed-wing UAV

An urban operation of unmanned aerial vehicles (UAVs) demands a high level of autonomy for tasks presented in a cluttered environment. While fixed-wing UAVs have been well suited for long-endurance missions at a high altitude, their navigation inside an urban area brings more challenges in motion planning and control. The inability to hover and low agility in motion cause more difficulties on planning a feasible path in a compact region, and a limited payload allows only low-grade sensors for state estimation and control.

[1]  Zhaodan Kong,et al.  Receding horizon trajectory optimization with a finite-state value function approximation , 2008, 2008 American Control Conference.

[2]  Mark H. Overmars,et al.  Coordinated motion planning for multiple car-like robots using probabilistic roadmaps , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[3]  Timothy W. McLain,et al.  Vector Field Path Following for Miniature Air Vehicles , 2007, IEEE Transactions on Robotics.

[4]  Takeo Kanade,et al.  Efficient Two-phase 3D Motion Planning for Small Fixed-wing UAVs , 2007, Proceedings 2007 IEEE International Conference on Robotics and Automation.

[5]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[6]  Mark Euston,et al.  A complementary filter for attitude estimation of a fixed-wing UAV , 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[7]  E. Feron,et al.  Real-time motion planning for agile autonomous vehicles , 2000, Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148).

[8]  O. Yakimenko.  Direct Method for Rapid Prototyping of Near-Optimal Aircraft Trajectories , 2000 .

[9]  John Canny,et al.  The complexity of robot motion planning , 1988 .

[10]  Anthony Stentz,et al.  A Guide to Heuristic-based Path Planning , 2005 .

[11]  Rudolph van der Merwe,et al.  The unscented Kalman filter for nonlinear estimation , 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

[12]  Dimitri P. Bertsekas,et al.  Dynamic Programming and Optimal Control, Two Volume Set , 1995 .

[13]  B. Mettler,et al.  Trajectory Interpolation for Parametrized Maneuvering and Flexible Motion Planning of Autonomous Vehicles , 2004 .

[14]  Bruno Sinopoli,et al.  Vision based navigation for an unmanned aerial vehicle , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[15]  Kenneth Y. Goldberg,et al.  Constant-Curvature Motion Planning Under Uncertainty with Applications in Image-Guided Medical Needle Steering , 2006, WAFR.

[16]  B. Mettler,et al.  Nonlinear trajectory generation for autonomous vehicles via parameterized maneuver classes , 2006 .

[17]  R. Zapata,et al.  Flying among obstacles , 1999, 1999 Third European Workshop on Advanced Mobile Robots (Eurobot'99). Proceedings (Cat. No.99EX355).

[18]  G. Swaminathan.  Robot Motion Planning , 2006 .

[19]  Konstantinos A. Tarabanis,et al.  A survey of sensor planning in computer vision , 1995, IEEE Trans. Robotics Autom..

[20]  Andrew G. Barto,et al.  Learning to Act Using Real-Time Dynamic Programming , 1995, Artif. Intell..

[21]  Howie Choset,et al.  Principles of Robot Motion: Theory, Algorithms, and Implementation ERRATA!!!! 1 , 2007 .

[22]  Takeo Kanade,et al.  Visual-inertial UAV attitude estimation using urban scene regularities , 2011, 2011 IEEE International Conference on Robotics and Automation.

[23]  Ignacy Duleba,et al.  3D Local Trajectory Planner for UAV , 2000, J. Intell. Robotic Syst..

[24]  Emilio Frazzoli,et al.  A hybrid control architecture for aggressive maneuvering of autonomous helicopters , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[25]  Emilio Frazzoli,et al.  Aggressive Maneuvering of Small Autonomous Helicopters: A Human-Centered Approach , 2001, Int. J. Robotics Res..