多水下机器人编队的组网通信方法研究

发布时间：2018-04-26 01:34

本文选题：水下机器人 + 编队航行　；参考：《电机与控制学报》2017年05期

【摘要】：使用水下机器人组网编队可以在更开阔的海域完成环境信息收集、区域搜索与快速环境感知等使命。为提高编队通信效率,研究了水声通信条件下多水下机器人组网通讯的方法。在多水下机器人的分层通信结构中,基于拓扑网络结构建立了信道传输模型。根据传输模型,对于距离领航员AUV节点较远而距离其他跟随AUV较近的节点采用线性拓扑传输方式,而对于其他AUV节点采用一对多竞争拓扑传输方式。在线性拓扑传输的自适应MAC协议中,领航员AUV和所有的跟随AUV通过广播与应答的方式实现时间同步,之后跟随AUV节点根据距离领航员AUV和数据传输的效果选择负责外围节点的通信或休眠,这就降低了领航AUV的能量消耗,提高了整个AUV编队组网的生存时间。而一对多竞争的自适应MAC协议包含了一种改进的握手机理,该协议可以降低传输的丢包率并提高网络的吞吐量。与AUV编队结合的通信仿真表明了该方法的先进性和有效性。
[Abstract]:The formation of underwater vehicles can complete the tasks of environmental information collection, regional search and rapid environmental awareness in the wider sea area. In order to improve the efficiency of formation communication, the communication method of multi-underwater vehicle network under underwater acoustic communication is studied. In the hierarchical communication structure of multiple underwater vehicles, a channel transmission model is established based on topological network structure. According to the transmission model, the linear topology transmission mode is used for the nodes which are far away from the AUV node of the navigator and closer to the other nodes following the AUV, while for the other AUV nodes, the one-to-many competing topology transmission mode is adopted. In the adaptive MAC protocol of linear topology transmission, the navigator AUV and all the following AUV realize time synchronization by broadcasting and answering. Then the following AUV nodes are chosen to be responsible for the communication or dormancy of the peripheral nodes according to the effect of the distance navigator AUV and data transmission. This reduces the energy consumption of the pilot AUV and improves the survival time of the whole AUV formation network. The adaptive MAC protocol of one-to-many competition includes an improved handshake mechanism, which can reduce packet loss rate and improve the throughput of the network. The communication simulation with AUV formation shows that the method is advanced and effective.
【作者单位】：哈尔滨工程大学水下机器人技术重点实验室;
【基金】：国家自然科学基金(5129050,51579053,61633009)
【分类号】：TP242

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