A Cooperative Dynamic Task Assignment Framework for COTSBot AUVs
This research provides a domain-specific solution for environmental protection, specifically for marine conservationists and roboticists working on autonomous intervention in delicate ecosystems.
This paper addresses the problem of controlling Crown-Of-Thorns Starfish (COTS) outbreaks in the Great Barrier Reef using Autonomous Underwater Vehicles (AUVs). It proposes a cooperative dynamic task assignment framework that utilizes a novel heuristic algorithm, Heuristic Fleet Cooperation (HFC), to maximize COTS eradication within a given mission time.
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.