Applied Sciences · 2018 · 41 citations · 24 references
EngineeringAutonomous SystemsRobotics EngineeringAutonomous VehiclesMarine RoboticsUnderwater RoboticsAutonomous Underwater VehiclesSubsea RoboticsAutonomous Underwater Vehicle SystemsCooperative HuntingCoordinationUnderwater Target Detection
The main challenge in multi‑AUV target hunting is designing motion paths and coordination mechanisms. This study aims to detect and surround a target in surface water using multiple autonomous underwater vehicles, proposing an integrated algorithm based on an improved potential field. The algorithm constructs a potential field from environmental data and incorporates dispersion, homodromous, and district‑difference degrees to enhance multi‑AUV cooperation, solving target hunting through this enriched field. Simulations demonstrate that the proposed approach is applicable and feasible for cooperative target hunting with multi‑AUVs.
In this paper, target hunting aims to detect target and surround the detected target in a surface-water using Multiple Autonomous Underwater Vehicles (multi-AUV) in a given area. The main challenge in multi-AUV target hunting is the design of AUV’s motion path and coordination mechanism. To conduct the cooperative target hunting by multi-AUV in a surface-water environment, an integrated algorithm based on improved potential field (IPF) is proposed. First, a potential field function is established according to the information of the surface-water environment. Then, the dispersion degree, the homodromous degree, and district-difference degree are introduced to increase the cooperation of the multi-AUV system. Finally, the target hunting is solved by embedding the three kinds of degree into the potential field function. The simulation results show that the proposed approach is applicable and feasible for multi-AUV cooperative target hunting.
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