Autonomous Underwater Vehicles

The oceans cover 70% of the Earth's surface and contain an abundance of living and nonliving resources that remain largely untapped waiting to be discovered. However, a number of complex issues, mainly caused by the nature of underwater environments, make exploration and protection of these resources difficult to perform. In the past few decades, various world-wide research and development activities in underwater robotic systems have increased in order to meet this challenge. Extensive use of ROVs is currently limited to a few applications because of very high operational costs and the need for human presence in conducting a mission. The demand for a more sophisticated underwater robotic technology that minimizes the cost and eliminates the need for human operator and is therefore capable of operating autonomously becomes apparent. These requirements led to the development of Autonomous Underwater Vehicles (AUVs). A key problem with autonomous underwater vehicles is being able to navigate in a generally unknown environment. The available underwater sensor suites have a limited capability to cope with such a navigation problem. In practice, no single sensor in the underwater environment can provide the level of accuracy, reliability and the coverage of information necessary to perform underwater navigation to cent percent safety. In order to navigate accurately an AUV needs to employ a navigation sensor with a high level of accuracy and reliability. It is therefore necessary to use a number of sensors and combine their information to provide the necessary navigation capability. To achieve this, a multisensor data fusion (MSDF) approach, which combines data from multiple sensors and related information from associated databases, can be used. The aim of this paper is to survey previous work and recent development in AUV navigation and to introduce MSDF techniques as a means of improving the AUV's navigation capability.

It has been suggested in this paper, from the various examples given in AUV navigation, that information coming from a single navigation system is not sufficient to provide a good navigation capability. Therefore MSDF techniques which combine sensory information from other navigation systems to improve the navigation capability is essential. MSDF techniques which combine sensory information from inertial, radio and optical navigation system to track underwater cables is currently being developed in a three year co-operative project funded by EPSRC involving both the University of Plymouth and Cranfield University, UK The navigation system that is being developed at the University of Plymouth utilizes INS/GPS and will be enhanced by a vision based navigation system being developed at Cranfield University.