Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow

This paper presents a nonlinear controller for a vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) that exploits a measurement optical flow to enable hover and landing control on a moving platform, such as, for example, the deck of a sea-going vessel. The VTOL vehicle is assumed to be equipped with a minimum sensor suite [i.e., a camera and an inertial measurement unit (IMU)], manoeuvring over a textured flat target plane. Two different tasks are considered in this paper. The first concerns the stabilization of the vehicle relative to the moving platform that maintains a constant offset from a moving reference. The second concerns regulation of automatic vertical landing onto a moving platform. Rigorous analysis of system stability is provided, and simulations are presented. Experimental results are provided for a quadrotor UAV to demonstrate the performance of the proposed control strategy.

[1]  S. Shankar Sastry,et al.  A vision system for landing an unmanned aerial vehicle , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[2]  Javaan Chahl,et al.  Biomimetic Visual Sensing and Flight Control , 2002 .

[3]  Nicolas Guenard.  Optimisation et implémentation de lois de commande embarquées pour la téléopération de micro drones aériens X4-flyer , 2007 .

[4]  Robert E. Mahony,et al.  The landing problem of a VTOL Unmanned Aerial Vehicle on a moving platform using optical flow , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  Nicolas H. Franceschini,et al.  Visually guided micro-aerial vehicle: automatic take off, terrain following, landing and wind reaction , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[6]  Mandyam V. Srinivasan,et al.  Landing Strategies in Honeybees and Applications to Uninhabited Airborne Vehicles , 2004, Int. J. Robotics Res..

[7]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[8]  Nick Barnes,et al.  A Robust Docking Strategy for a Mobile Robot Using Flow Field Divergence , 2006, IEEE Transactions on Robotics.

[9]  Nicolas H. Franceschini,et al.  Optic flow regulation: the key to aircraft automatic guidance , 2005, Robotics Auton. Syst..

[10]  Valery A. Ugrinovskii,et al.  Prediction of vertical motions for landing operations of UAVs , 2008, 2008 47th IEEE Conference on Decision and Control.

[11]  R. Mahony,et al.  Robust trajectory tracking for a scale model autonomous helicopter , 2004 .

[12]  Svetha Venkatesh,et al.  How honeybees make grazing landings on flat surfaces , 2000, Biological Cybernetics.

[13]  Paul Y. Oh,et al.  Optic-Flow-Based Collision Avoidance , 2008, IEEE Robotics & Automation Magazine.

[14]  J. Koenderink,et al.  Facts on optic flow , 1987, Biological Cybernetics.

[15]  Robert E. Mahony,et al.  A Practical Visual Servo Control for an Unmanned Aerial Vehicle , 2008, IEEE Transactions on Robotics.

[16]  Tarek Hamel,et al.  Stability Analysis of an UAV Controller using Singular Perturbation Theory , 2008 .

[17]  Kenzo Nonami,et al.  Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles , 2009, Robotics Auton. Syst..

[18]  Dario Floreano,et al.  Vision-based control of near-obstacle flight , 2009, Auton. Robots.

[19]  Tarek Hamel,et al.  Dynamic Image-Based Visual Servo Control Using Centroid and Optic Flow Features , 2008 .

[20]  Kimon P. Valavanis,et al.  Advances in Unmanned Aerial Vehicles , 2007 .

[21]  S. Umeyama,et al.  Least-Squares Estimation of Transformation Parameters Between Two Point Patterns , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Richard M. Murray,et al.  Pitch-Altitude Control and Terrain Following Based on Bio-Inspired Visuomotor Convergence , 2005 .

[23]  Robert E. Mahony,et al.  Visual servoing of an under-actuated dynamic rigid-body system: an image-based approach , 2002, IEEE Trans. Robotics Autom..

[24]  Lorenzo Marconi,et al.  Autonomous vertical landing on an oscillating platform: an internal-model based approach , 2002, Autom..

[25]  Matthew Garratt,et al.  Biologically inspired climbing with a hexapedal robot , 2008 .

[26]  Kaustubh Pathak,et al.  Approaches for a tether-guided landing of an autonomous helicopter , 2006, IEEE Transactions on Robotics.

[27]  Gaurav S. Sukhatme,et al.  Visually guided landing of an unmanned aerial vehicle , 2003, IEEE Trans. Robotics Autom..

[28]  Helene Piet-Lahanier,et al.  A hierarchical controller for miniature VTOL UAVs: Design and stability analysis using singular perturbation theory , 2011 .

[29]  David J. Fleet,et al.  Performance of optical flow techniques , 1994, International Journal of Computer Vision.

[30]  P. Olver.  Nonlinear Systems , 2013 .

[31]  Tarek Hamel,et al.  Attitude and gyro bias estimation for a flying UAV , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[32]  Hans J. Schneebeli,et al.  A general approach for egomotion estimation with omnidirectional images , 2002, Proceedings of the IEEE Workshop on Omnidirectional Vision 2002. Held in conjunction with ECCV'02.