Comparison of lateral controllers for following linear structures using computer vision

This paper presents a comparison of lateral controllers for vision-based control of a small autonomous aircraft following a road. Control strategies are designed to stabilize the aircraft lateral control using only the vision measurements and inertial sensors. Methods compared here include several aim-ahead controllers, sliding surface controllers, linear quadratic Gaussian (LQG) regulators, and a receding horizon controller (RHC). Simulation results are given comparing the controllers under ideal conditions as well as with background wind, a zero-roll assumption in the vision system, and realistic quantization of the control output by the low-level flight control system

[1]  Zu Whan Kim.  Realtime Road Detection by Learning from One Example , 2005, 2005 Seventh IEEE Workshops on Applications of Computer Vision (WACV/MOTION'05) - Volume 1.

[2]  Marius Niculescu,et al.  LATERAL TRACK CONTROL LAW FOR AEROSONDE UAV , 2001 .

[3]  Javaan Chahl,et al.  Biologically inspired visual sensing and flight Control , 2003, The Aeronautical Journal (1968).

[4]  Xiao Xiao,et al.  Vision-based road-following using a small autonomous aircraft , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[5]  R. Sengupta,et al.  Vision Based Following of Locally Linear Structures using an Unmanned Aerial Vehicle , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[6]  E.N. Johnson,et al.  Recent flight test results of active-vision control systems , 2005, Proceedings of the 2005, American Control Conference, 2005..

[7]  Gaurav S. Sukhatme,et al.  A comparison of two camera configurations for optic-flow based navigation of a UAV through urban canyons , 2004, 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (IEEE Cat. No.04CH37566).

[8]  Eric W. Frew,et al.  Flight Demonstrations of Self-directed Collaborative Navigation of Small Unmanned Aircraft , 2004 .

[9]  Claire J. Tomlin,et al.  Autopilot Design for the Stanford DragonFly UAV: Validation through Hardware-in-the-Loop Simulation* , 2001 .

[10]  Patrick Rives,et al.  A fast vision-based road following strategy applied to the control of aerial robots , 2001, Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing.

[11]  S. Rock,et al.  Passive GPS-Free Navigation for Small UAVs , 2005, 2005 IEEE Aerospace Conference.

[12]  Stefano Soatto,et al.  A lagrangian formulation of nonholonomic path following , 1997, Block Island Workshop on Vision and Control.

[13]  Jitendra Malik,et al.  A real-time approach to stereopsis and lane-finding , 1996, Proceedings of Conference on Intelligent Vehicles.

[14]  T. Kanade,et al.  Real-time and 3D vision for autonomous small and micro air vehicles , 2004, 2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601).

[15]  Eric W. Frew.  Receding Horizon Control Using Random Search for UAV Navigation with Passive, Non-cooperative Sensing , 2005 .

[16]  J. Langelaan,et al.  Navigation of Small UAVs Operating in Forests , 2004 .

[17]  Robert E. Mahony,et al.  Image-based visual servo control of aerial robotic systems using linear image features , 2005, IEEE Transactions on Robotics.