Early Warning Obstacle Avoidance-Enabled Path Planning for Multi-AUV-Based Maritime Transportation Systems

Abstract

As a prototype of the underwater Internet of Things-enabled maritime transportation systems, multi-Autonomous Underwater Vehicle (AUV)-based Underwater Wireless Networks (UWNs) have become an important research topic due to their distribution and robustness. In this paper, the concept of multi-AUV-based UWNs is first defined, where AUV is regarded as a network node, and communication among the AUVs is the potential network links. Then, to improve network scalability and controllability, a paradigm of Software Defined multi-AUV-based UWNs (SD-UWNs) is proposed, where the Software Defined Network (SDN) technique is used to upgrade the UWN architecture by directing intelligent network functions. Topology and artificial potential field theories are applied to construct a network control model for the SD-UWNs. Based on the efficient data sharing ability of the SD-UWNs, an early warning obstacle avoidance-enabled path planning scheme is proposed to guarantee safe sailing of the SD-UWNs, where comprehensive obstacle avoidance scenarios are taken into account. Simulation results demonstrate that the proposed method is effective in planning the cooperative operation for the SD-UWNs and is capable of performing accurate and reliable obstacle avoidance tasks.