A cooperative control framework of multiple unmanned aerial vehicles for dynamic oil spill cleanup

Oil spills within the marine environment are undesirable events caused by unavoidable economic activities of huge sea lane traffics. A tremendous effort has been made to tackle this problem within academia and industries; among them, the concept of autonomous vehicles for oil spill combating seems to provide a promising solution. This paper mainly proposes a cooperative deployment framework for unmanned aerial vehicles (UAVs) to perform oil spill cleanup missions with dispersant spraying. An appropriate oil density function is introduced by applying a Gaussian mixture model based on NOAA's advanced oil spill model (General NOAA Operational Modeling Environment). UAVs are then deployed to cover oil spills for spraying operations. This deployment problem is formulated as a coverage problem based on centroidal Voronoi tessellation to determine UAVs' optimal location. By transforming the coverage control problem into a target tracking one, an Integral Terminal Super Twisting Sliding Mode Control is provided to drive the UAVs to the optimal configuration. Furthermore, a novel spraying adjustment strategy is also designed to target the oil spills more accurately at the appropriate dosage. The effectiveness of the proposed framework is studied through a case study in the Abuzar oil field in the Persian Gulf. The results verify the performance of the cooperative oil spill cleanup framework in conjunction with advanced oil spill modeling. Moreover, it is concluded that the oil spill can be more effectively dispersed if the proposed spraying adjustment strategy is implemented.

Automated summary

The paper proposes a cooperative deployment framework for UAVs to clean up oil spills, utilizing Gaussian mixture models and Voronoi tessellation for optimal location determination, along with a spraying adjustment strategy for more effective dispersal of oil spills.