  This paper presents a cooperative dynamic task assignment framework for a
certain class of Autonomous Underwater Vehicles (AUVs) employed to control
outbreak of Crown-Of-Thorns Starfish (COTS) in Australia's Great Barrier Reef.
The problem of monitoring and controlling the COTS is transcribed into a
constrained task assignment problem in which eradicating clusters of COTS, by
the injection system of COTSbot AUVs, is considered as a task. A probabilistic
map of the operating environment including seabed terrain, clusters of COTS,
and coastlines is constructed. Then, a novel heuristic algorithm called
Heuristic Fleet Cooperation (HFC) is developed to provide a cooperative
injection of the COTSbot AUVs to the maximum possible COTS in an assigned
mission time. Extensive simulation studies together with quantitative
performance analysis are conducted to demonstrate the effectiveness and
robustness of the proposed cooperative task assignment algorithm in eradicating
the COTS in the Great Barrier Reef.
