The general objective of the work described in this chapter was to design and to develop cost-efficient technology for the inspection of pipelines and submarine cables in maritime infrastructures, including the development of an autonomous and safe navigation system for a submarine prototype. With this prototype it will also be possible to make pattern recognition from sonar's data to detect debris in the proximity of the target to be tracked. The design considerations and proposed solutions as well as a description of the hardware employed, the sensors in the payload, and the DMP based on an expert system are presented in this section.
The specific aims of this development were the following ones:
• To develop a software module to provide the desired trajectory for an AUV devoted to submarine pipeline and cable tracking with the purpose of inspecting them, resorting to artificial intelligence techniques, particularly knowledge based systems (KBS) and artificial neural networks (ANN). The initial point was the EN4AUV (Expert Navigation for Autonomous Underwater Vehicle) in (Acosta et al., 2003). This module will be more thoroughly described in section 3.5.
• To assemble a low-cost prototype, including a MBE sonar, a SSS sonar, a GPS, an INS, and an industrial PC type as processing unit.
• To develop a pattern recognition system based on artificial neural networks for classifying objects using the data provided by the sonars.
• To validate the resulting prototype by means of its utilization in the sea for carrying out inspections of pipelines and submarine cables to a depth not bigger than 100m.
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