Open Access Open Access  Restricted Access Subscription Access

Optimal Path Planning for Small UAVs in Wind

Sikha Hota, Debasish Ghose


This paper proposes an optimal path planning strategy that enables an Unmanned Air Vehicle (UAV) to converge to a rectilinear path starting from any arbitrary but known initial position and orientation. The vehicle is constrained by its minimum turn radius. During the flight the altitude and
airspeed are held constant. This is a 2-dimensional modified Dubins problem and unlike in the classical Dubins problem, the final point and orientation are not specified. However, the straight line on which the final point should be is specified. Based on the kinematic properties of the vehicle, generation of optimal path is discussed both in the constant and time-varying wind condition. Using a full 6-DOF simulink model of an UAV this generated optimal path is tracked by autopilot consisting of proportional-integralderivative (PID) controllers. The longitudinal and lateral dynamics are assumed to be decoupled and the velocity and altitude are held constant with the help of the longitudinal autopilot. The simulation results show path generation and tracking for a few sample cases.

Full Text:



L.E. Dubins, On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents,

American Journal of Mathematics, 79 (1957) 497-516.

J.A. Reeds and L.A. Sheep, Optimal paths for a car that goes both forwards and backwords, Pacific Journal of Mathematics, 145 (1990) 367-393.

J.D. Boissonnat, A. Cerezo and J. Leblond, Shortest paths of bounded curvature constraints, Journal of Intelligent and Robotic Systems, 11, No 1-2, 5-20,1994.

A.M. Shkel and V.J. Lumelsky, Classification of Dubins set, Robotics and Autonomous Systems, 34 (2001) 179-202.

H.Wong, V. Kapila, and R. Vaidyanathan, UAV optimal path planning using C - C - C class paths for target touring, 43rd IEEE Conference on Decision and Control, December 14-17, 2004, Atlantis, Paradise Island, Bahamas.

T.G. McGee, S. Spry, and K. Hedrick, Optimal path planning in a constant wind with a bounded turning rate, Proc. of the AIAA Guidance, Navigation and Control Conference and Exhibit, San Francisco, CA,

August 2005.

S. Hota and D. Ghose, “A modified Dubins method for optimal path planning of a miniature air vehicle converging to a straight line path", Proceedings of the American Control Conference, St. Louis, Missouri, USA, June 2009, pp 2397-2402.

J. Osborne and R. Rysdyk, Waypoint guidance for small UAVs in wind, AIAA Infotech@Aerospace, Arlington, Virginia, 2005.

R.Rysdyk, UAV Path Following for constant line-ofsight, 2nd AIAA “Unmanned Unlimited” Systems,Technologies, and Operations Aerospace,

Land, and Sea Conference, Paper 6626, September, 2003, San-Diego, CA.

D.R. Nelson, D.B. Barber, T.W. Mclain and R. W. Beard, Vector field path following for miniature air vehicle, IEEE Transactions on Robotics, vol. 23, No. 3, June 2007.

H. Chitsaz and S.M. LaValle, Time-optimal Paths for a Dubins airplane, Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, LA, USA, Dec. 12-14, 2007.

S. Hota and D. Ghose, Rectilinear Path Following in 3D Space, 7th International Conference on Computational Intelligence, Robotics and

Autonomous Systems, September 2010, Bangalore, India. (Accepted).

S. Hota and D. Ghose, Optimal path planning for an aerial vehicle in 3D space, 49th IEEE Conference on Decision and Control, Atlanta, USA, Dec 2010. (Accepted)

S. Hota and D. Ghose, Optimal geometrical path in 3D with curvature constraint, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2010), Taipei, Taiwan, 18-22 October. (Accepted)

W. Ren, R. W. Beard, Trajectory tracking for unmanned air vehicles with velocity and heading rate constraints, IEEE Transactions on Control Systems Technology, vol. 12, no. 5, September 2004, pp 706-716.

V Ghadiok, D. Ghose, Study of multi-agent consensus under pursuit strategies applied to autonomous UAV swarms, Technical Report, DRDO-IISc Progamme on Advanced Research in Mathematical Engineering,

July 2008.

MAGICC Lab, Brigham Young University.



  • There are currently no refbacks.