Sidescan Sonar has been the most popular probe for sea floor detecting in the underwater engineering. It is not only use to map the topography of the sea floor but also apply to the underwater search and rescue. Sidescan Sonar relies on commercial software, e.g. SonarPro, to record the raw data and draw images of the sea floor. However, SonarPro only presents the data to display segmental images, but it can not illustrate all images of the sea floor in one drawing. Researchers need to use the other software, called WizMap, to mosaic all Sidescan images in one drawing. WizMap is powerful for analyzing Sidescan data, but it is costly and has never been published its technology of Sidescan mosaic images. Thus we can not understand how Wizmap analysis raw data and make a mosaic drawing. Moreover, we could only accept the results it made, even the mosaic drawing is not correct. In this study, we implement a new analysis software package to facilitate reading raw data and drawing mosaic images of Sidescan Sonar. Sidescan Sonar provides basic function to record all digital raw data including GPS position, heading, roll, pitch, etc. We transfer the ship and Sidescan location from GPS to TM2 coordinate and illustrate the two side images along Sidescan trace in the same drawing. We will review the drawing and check all characteristics of these images and then adjust the heading offset and location offset to fit a better mosaic drawing. Finally, we combine all images into one mosaic drawing and compare two drawings between WizMap mosaic image and our mosaic drawing for confirming all results.

The proposed project is the simulation of a system to search for air vehicles which have splashed-down in the ocean. The system comprises a group of 10+ autonomous underwater vehicles, which cooperate in order to locate the aircraft. The search algorithm used in this system is based on a quadratic Newton method and was developed at Sandia National Laboratories. The method has already been successfully applied to several two dimensional problems at Sandia. The original 2D algorithm was converted to 3D and tested for robustness in the presence of sensor error, position error and navigational error. Treating the robots as point masses, the system was found to be robust for all such errors. Several real-life adaptations were necessary. A round-robin communication strategy was implemented on the system to properly simulate the dissemination of information throughout the group. Time to convergence is delayed but the system still functioned adequately. Once simulations for the point masses had been exhausted, the dynamics of the robots were included. The robot equations of motion were described using Kane's equations. Path-planning was investigated using optimal control methods. The Variational Calculus approach was attempted using a line search tool "fsolve" found in Matlab and a Genetic Algorithm. A dynamic programming technique was also investigated using a method recently developed by Sandia National Laboratories. The Dynamic Programming with Interior Points (DPIP) method was a very effcient method for path planning and performed well in the presence of system constraints. Finally all components of the system were integrated. The motion of the robot exactly matched the motion of the particles, even when subjected to the same robustness tests carried out on the point masses. This thesis provides exciting developments for all types of cooperative projects.