A vision-based interactive system for underwater robots

A vision based system is developed for interaction between the man-robot unit and robot-robot unit in underwater environments. Vision is the communicating medium between the agents. The image consists of an ON/OFF light pattern produced by a set of electro-luminescent panels, representing a particular command. The vision system introduced in this paper recognizes these patterns under the defined environmental conditions. In the image processing system the Hough transform is performed with the Sobel operator to extract important features of the image. The decision making time of this system is approximately 1 sec on a transputer based hardware, which is equivalent to the CPU system on the testbed robot, "The Twin-Burger". This decision making time is acceptable for slowly moving underwater robots. In order to track the region of interest, the vision system calculates the pan and tilt angles of the CCD camera. The system is tested for different situations underwater as well as in air.

[1]  Tamaki Ura,et al.  Development of a versatile test-bed "Twin-Burger" toward realization of intelligent behaviors of autonomous underwater vehicles , 1993, Proceedings of OCEANS '93.

[2]  Takeo Kanade,et al.  Visual tracking of a moving target by a camera mounted on a robot: a combination of control and vision , 1993, IEEE Trans. Robotics Autom..

[3]  Tamaki Ura,et al.  Multi-sensor based AUV with distributed vehicle management architecture , 1992, Proceedings of the 1992 Symposium on Autonomous Underwater Vehicle Technology.

[4]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[5]  Hon Fung Li,et al.  Shapes Recognition Using the Straight Line Hough Transform: Theory and Generalization , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Josef Kittler,et al.  A survey of the hough transform , 1988, Comput. Vis. Graph. Image Process..

[7]  Allen R. Hanson,et al.  Extracting Straight Lines , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Gregory D. Hager,et al.  Real-time vision-based robot localization , 1993, IEEE Trans. Robotics Autom..