Mosaic-based navigation for autonomous underwater vehicles

We propose an approach for vision-based navigation of underwater robots that relies on the use of video mosaics of the sea bottom as environmental representations for navigation. We present a methodology for building high-quality video mosaics of the sea bottom in a fully automatic manner, which ensures global spatial coherency. During navigation, a set of efficient visual routines are used for the fast and accurate localization of the underwater vehicle with respect to the mosaic. These visual routines were developed taking into account the operating requirements of real-time position sensing, error bounding, and computational load. A visual servoing controller, based on the vehicle's kinematics, is used to drive the vehicle along a computed trajectory, specified in the mosaic, while maintaining constant altitude. The trajectory toward a goal point is generated online to avoid undefined areas in the mosaic. We have conducted a large set of sea trials, under realistic operating conditions. This paper demonstrates that without resorting to additional sensors, visual information can be used to create environment representations of the sea bottom (mosaics) and support long runs of navigation in a robust manner.

[1]  Alonzo Kelly,et al.  Mosaicing large cyclic environments for visual navigation in autonomous vehicles , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[2]  J. Folcher,et al.  Identification and control of the Phantom 500 body motion , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[3]  José Santos-Victor,et al.  Underwater Video Mosaics as Visual Navigation Maps , 2000, Comput. Vis. Image Underst..

[4]  François Chaumette,et al.  2 1/2 D Visual Servoing with Respect to Unknown Objects Through a New Estimation Scheme of Camera Displacement , 2000, International Journal of Computer Vision.

[5]  Jonathan C. Howland,et al.  Quantitative photomosaicking of underwater imagery , 1998, IEEE Oceanic Engineering Society. OCEANS'98. Conference Proceedings (Cat. No.98CH36259).

[6]  Harpreet S. Sawhney,et al.  Robust Video Mosaicing through Topology Inference and Local to Global Alignment , 1998, ECCV.

[7]  Peter I. Corke,et al.  A tutorial on visual servo control , 1996, IEEE Trans. Robotics Autom..

[8]  Janne Heikkilä,et al.  A four-step camera calibration procedure with implicit image correction , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Patrick Rives,et al.  A new approach to visual servoing in robotics , 1992, IEEE Trans. Robotics Autom..

[10]  Takeo Kanade,et al.  Optical Navigation by the Method of Differences , 1985, IJCAI.

[11]  Stephen M. Rock,et al.  Demonstration of a vision-based dead-reckoning system for navigation of an underwater vehicle , 1998, Proceedings of the 1998 Workshop on Autonomous Underwater Vehicles (Cat. No.98CH36290).

[12]  Wim H. Hesselink,et al.  A General Algorithm for Computing Distance Transforms in Linear Time , 2000, ISMM.

[13]  William H. Press,et al.  Numerical Recipes in FORTRAN - The Art of Scientific Computing, 2nd Edition , 1987 .

[14]  Olivier Faugeras,et al.  Motion and Structure from Motion in a piecewise Planar Environment , 1988, Int. J. Pattern Recognit. Artif. Intell..

[15]  José Santos-Victor,et al.  Trajectory reconstruction with uncertainty estimation using mosaic registration , 2001, Robotics Auton. Syst..

[16]  Saburo Tsuji,et al.  Panoramic representation for route recognition by a mobile robot , 1992, International Journal of Computer Vision.

[17]  S. van der Zwaan,et al.  Real-time vision-based station keeping for underwater robots , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[18]  William A. Barrett,et al.  Globally Optimal Image Mosaics , 1998, Graphics Interface.

[19]  Shahriar Negahdaripour,et al.  Positioning and photo-mosaicking with long image sequences; comparison of selected methods , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[20]  Francis L. Merat,et al.  Introduction to robotics: Mechanics and control , 1987, IEEE J. Robotics Autom..

[21]  Sjoerd Van Der Zwaan.  Vision Based Station Keeping And Docking For Floating Robots , 2001 .

[22]  Ryan M. Eustice,et al.  Image registration underwater for fluid flow measurements and mosaicking , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[23]  Emanuele Trucco,et al.  Feature Tracking in Video and Sonar Subsea Sequences with Applications , 2000, Comput. Vis. Image Underst..

[24]  Bill Triggs,et al.  Autocalibration from Planar Scenes , 1998, ECCV.

[25]  Gérard G. Medioni,et al.  A graph-based global registration for 2D mosaics , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[26]  Xavier Cufí,et al.  Augmented state Kalman filtering for AUV navigation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[27]  Yoshiaki Shirai,et al.  Three-Dimensional Computer Vision , 1987, Symbolic Computation.

[28]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[29]  Alonzo Kelly.  Mobile Robot Localization from Large-Scale Appearance Mosaics , 2000, Int. J. Robotics Res..

[30]  Emanuele Trucco,et al.  Dynamic Video Mosaics and Augmented Reality for Subsea Inspection and Monitoring , 2000 .

[31]  Christopher G. Harris,et al.  A Combined Corner and Edge Detector , 1988, Alvey Vision Conference.

[32]  S. Negahdaripour,et al.  3-D motion and depth estimation from sea-floor images for mosaic-based station-keeping and navigation of ROVs/AUVs and high-resolution sea-floor mapping , 1998, Proceedings of the 1998 Workshop on Autonomous Underwater Vehicles (Cat. No.98CH36290).

[33]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[34]  Roger Y. Tsai,et al.  A versatile camera calibration technique for high-accuracy 3D machine vision metrology using off-the-shelf TV cameras and lenses , 1987, IEEE J. Robotics Autom..

[35]  Giulio Sandini,et al.  Foveated active tracking with redundant 2D motion parameters , 2002, Robotics Auton. Syst..

[36]  Robert M. Haralick,et al.  Propagating covariance in computer vision , 1994, Proceedings of 12th International Conference on Pattern Recognition.

[37]  Alexandre Bernardino,et al.  Visual station keeping for floating robots in unstructured environments , 2002, Robotics Auton. Syst..

[38]  Laurence A. Wolsey,et al.  Integer and Combinatorial Optimization , 1988, Wiley interscience series in discrete mathematics and optimization.

[39]  Xun Xu,et al.  Application of extended covariance intersection principle for mosaic-based optical positioning and navigation of underwater vehicles , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[40]  Xun Xu,et al.  Vision-based rov system , 2000 .