Optimal docking pose and tactile hook-localisation strategy for AUV intervention: The DIFIS deployment case

The DIFIS project has proposed a new solution for the immediate intervention directly on tanker wrecks so as to contain any leakages and prevent eventual pollution. The method could be extended also to oil well-blow-out cases such as the recent accident in the Gulf of Mexico. The DIFIS deployment typically requires the use of ROVs and dedicated dynamic-positioning ships that increase the cost significantly and make the operations weather-dependent. Eventual AUV use would result in much more efficient and flexible deployment procedures. The scenario studied here consists of a hook-grasping task that is part of the DIFIS mooring procedure. The overall objective is to automate certain processes enabling the use of AUVs or, at least, enhancing the currently foreseen ROV operations. A two-step method is presented consisting of a genetic algorithm for the determination of the optimum docking pose for the vehicle, and a particle filter algorithm that runs on a later stage for the tactile localisation of the hook. The method proposed is rather generic and can be extended to several steps of the DIFIS Deployment procedure, or even to other AUV intervention missions in a semi-structured environment. Results from the two algorithms are also presented and discussed.

► We attempt to automate underwater operations, enable the use of AUVs and enhance ROV operations. ► The method could be extended to other AUV intervention missions in semi-structured environments. ► Assist on performing autonomous target localisation and manipulation on site. ► Combine GA to find best docking pose and tactile-sensing to localise the hook. ► We guarantee minimum dexterity for the manipulator and minimise travel distance for the UUV.