The sea occupies the most part of the earth. It accounts for about 70% of the total area of the earth with an enormous amount of marine resources divided largely into fishery resources, marine mineral resources, and marine energy resources.
Though Korea is surrounded by the sea with this huge amount of resources on three sides, in reality the country lacks studies on marine development.
As the marine development cannot be made by human beings in person, the Romotely Operated Vehicle (ROV) or Atonomous Underwater Vehicle (AUV) is used. However, there are many limitations in underwater work.
What is the representative of the many limitations of underwater work by human beings is the oxygen deficiency and limitations on activity because of underwater pressure. The human body cannot store oxygen under the stimulation of high pressure not like under the environmental stimulations (high temperature, low temperature, exposure to highlands, and so on). Some mammals like seals can submerge to a depth of 240 m without a problem, but human beings have restrictions in underwater activities unless they use an artificial object and their ability to store oxygen gets decreased because of high pressure.
There are many difficulties for human beings to see the state of underwater environment in person and for underwater robots to autonomously drive. The underwater environment has various obstacles such as gorges whose size not known, rocks, sunken ship, and so on with a great variety of shape and size.
In the environment where human beings live, there is no problem in using eletromagnetic waves such as Bluetooth and wireless Internet, but they become useless underwater. However, ultrasonic waves, which are faster and moves further than electromagnetic waves, are used underwater.
This paper aims to propose the method to detect the shape of underwater obstacles by using the Radial Underwater Ultrasonic Sensor (RUUS) as a way to make the aquanautics smoother.
It is intended to verify the performances on the shape of underwater obstacles and similarity of actual obstacles detected by using the RUUS proposed in this study.