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This paper addresses the problem of Internet of Underwater Things (IoUT) information collection using an unmanned marine vehicles (UMVs) system. A time-synchronized distributed method (TSDM) is proposed to address the distributed Dubins traveling salesman problem (DTSP) using unmanned surface vehicle (USV) and autonomous underwater vehicles (AUVs). Information collection missions are allocated to a hybrid algorithm that combines cluster and ant colony optimization (ACO) via a single USV and multiple AUVs. A pseudo-trajectory homotopy method (PTHM) has been developed to optimize the paths associated with the diving and rising of AUVs under kinematic constraints. An AUV information collection path planning (ICPP) algorithm is presented to optimize the paths and enhance the efficiency of information collection from sensor nodes for AUVs. A Dubins obstacle avoidance algorithm is proposed to reduce the impact of obstacles for path planning. Based on the TSDM, the AUVs are recovered by the USV when they ascend to the surface. The simulation results demonstrate that the UMVs system and path planning strategy effectively address the challenges of information collection path planning in the IoUT, particularly under the constraints of underwater communication.
Yang et al. (Wed,) studied this question.