A FRAMEWORK FOR COOPERATIVE DYNAMIC TASK ASSESSMENT FOR COTSBOT AUVs

This project presents a proposed framework aimed at collaborative and dynamic allocation of tasks for a specific group of self-governing underwater vehicles known as autonomous underwater vehicles (AUVs). These AUVs are utilized to manage the proliferation of Crown-Of-Thorns starfish (COTS) on the Great Barrier Reef situated in Australia. The concept of constrained task allocation is employed to reframe the supervision and regulation of COTS into a challenge where a central task involves eradicating clusters of COTS using the injection mechanism integrated into the COTSbot AUVs. The operational setting, encompassing underwater topography, COTS clusters, and shorelines, is mapped probabilistically. The COTSbot AUVs are then collaboratively deployed to target as many COTS clusters as possible within a designated mission timeframe, utilizing an inventive heuristic technique termed Heuristic Fleet Cooperation (HFC). To substantiate the efficiency and dependability of the proposed collaborative task allocation algorithm for COTS eradication in the Great Barrier Reef, comprehensive simulations and quantitative performance evaluations are conducted.