Automatic visual station keeping of an underwater robot

This paper presents a method for drift-free station keeping of an underwater robot using computer vision. The sensing problem is simplified by assuming an active control system can be used to keep positional errors small. Robot position is obtained by tracking texture features using image filtering and correlation. Errors in four degrees of freedom (translation and yaw) are determined in real time and are fed into a robot control system to accomplish the task of station keeping. Experimental results demonstrating sensing quality and robot station keeping are presented.<<ETX>>

[1]  Rama Chellappa,et al.  Automatic feature point extraction and tracking in image sequences for unknown camera motion , 1993, 1993 (4th) International Conference on Computer Vision.

[2]  Shahriar Negahdaripour,et al.  Improved methods for undersea optical stationkeeping , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[3]  Shahriar Negahdaripour,et al.  Passive Optical Sensing For Near-bottom Stationkeeping , 1990, Conference Proceedings on Engineering in the Ocean Environment.

[4]  Don Brutzman,et al.  Tactical/execution level coordination for hover control of the NPS AUV II using onboard sonar servoing , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).

[5]  James L. Crowley,et al.  Position estimation for a mobile robot using vision and odometry , 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

[6]  H. K. Nishihara,et al.  Practical Real-Time Imaging Stereo Matcher , 1984 .

[7]  Shahriar Negahdaripour,et al.  Undersea optical stationkeeping: Improved methods , 1991, J. Field Robotics.

[8]  R. L. Marks,et al.  Automatic object tracking for an unmanned underwater vehicle using real-time image filtering and correlation , 1993, Proceedings of IEEE Systems Man and Cybernetics Conference - SMC.

[9]  Shahriar Negahdaripour,et al.  Optical sensing for undersea robotic vehicles , 1991, Robotics Auton. Syst..

[10]  Shahriar Negahdaripour,et al.  Recovering shape and motion from undersea images , 1990 .

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

[12]  Carlo Tomasi,et al.  Direction of heading from image deformations , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[13]  Shahriar Negahdaripour,et al.  Passive Vision Sensing Techniques for Autonomous Undersea Vehicles , 1989, IAS.

[14]  Hiroshi Ishiguro,et al.  Computationally inexpensive egomotion determination for a mobile robot using an active camera , 1991, Proceedings. 1991 IEEE International Conference on Robotics and Automation.

[15]  J. S. Fox Stationkeeping Using Optical Ranging Of Natural Features , 1989, Proceedings OCEANS.

[16]  池内 克史 A Practical Realtime Imaging Stereo Matcher , 1984 .

[17]  R. L. Marks,et al.  Real-time video mosaicking of the ocean floor , 1994, Proceedings of IEEE Symposium on Autonomous Underwater Vehicle Technology (AUV'94).