Simulation program complex for studying motion control methods for autonomous underwater vehicles

Development of a graphical simulation complex for studying motion control methods for autonomous underwater vehicles is discussed. Its structure and functioning scheme are presented. An approach to solving navigation problem and to 3D reconstruction of underwater environment from a given sequence of digital images is described. It is based on the use of an extended Kalman filter and original algorithm of dense 3D recovery of the environment points. Results of computational experiments and estimates of the efficiency of the approach are presented.

[1]  Don Brutzman,et al.  Virtual world visualization for an autonomous underwater vehicle , 1995, 'Challenges of Our Changing Global Environment'. Conference Proceedings. OCEANS '95 MTS/IEEE.

[2]  Takeo Kanade,et al.  A Multiple-Baseline Stereo , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  João Borges de Sousa,et al.  A simulation environment for the coordinated operation of multiple autonomous underwater vehicles , 1997, WSC '97.

[4]  Olivier Faugeras,et al.  3D Dynamic Scene Analysis , 1992 .

[5]  John J. Leonard,et al.  Towards Constant-Time SLAM on an Autonomous Underwater Vehicle Using Synthetic Aperture Sonar , 2003, ISRR.

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

[7]  Christopher G. Harris,et al.  3D positional integration from image sequences , 1988, Image Vis. Comput..

[8]  G. Bruzzone,et al.  A simulation environment for unmanned underwater vehicles development , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[9]  S. T. Tuohy A simulation model for AUV navigation , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).

[10]  Nicholas Ayache,et al.  Artificial vision for mobile robots - stereo vision and multisensory perception , 1991 .

[11]  Alexandre Bernardino,et al.  Mosaic-based navigation for autonomous underwater vehicles , 2003 .

[12]  Anders Heyden,et al.  Simplified intrinsic camera calibration and hand-eye calibration for robot vision , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[13]  Berthold K. P. Horn,et al.  Closed-form solution of absolute orientation using unit quaternions , 1987 .

[14]  Carlo Tomasi,et al.  Good features to track , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[15]  Andrew Hogue,et al.  Underwater 3D Mapping: Experiences and Lessons learned , 2006, The 3rd Canadian Conference on Computer and Robot Vision (CRV'06).

[16]  Olivier Faugeras,et al.  Three D-Dynamic Scene Analysis: A Stereo Based Approach , 1992 .