State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China.
Sensors (Basel). 2019 Sep 21;19(19):4089. doi: 10.3390/s19194089.
The advent of the swarm makes it feasible to dynamically monitor a wide area for maritime applications. The crucial problems of underwater swarm monitoring are communication and behavior coordination. To tackle these problems, we propose a wide area monitoring strategy that searches for static targets of interest simultaneously. Traditionally, an underwater robot adopts either acoustic communication or optical communication. However, the former is low in bandwidth and the latter is short in communication range. Our strategy coordinates underwater robots through indirect communication, which is inspired by social insects that exchange information by pheromone. The indirect communication is established with the help of a set of underwater communication nodes. We adopt a virtual pheromone-based controller and provide a set of rules to integrate the area of interest into the pheromone. Based on the information in the virtual pheromone, behavior laws are developed to guide the swarm to monitor and search with nearby information. In addition, a robot can improve its performance when using additional far-away pheromone information. The monitoring strategy is further improved by adopting a swarm evolution scheme which automatically adjusts the visiting period. Experimental results show that our strategy is superior to the random strategy in most cases.
蜂群技术的出现使得对海洋应用进行大范围的动态监测成为可能。水下蜂群监测的关键问题是通信和行为协调。为了解决这些问题，我们提出了一种同时搜索静态感兴趣目标的大面积监测策略。传统上，水下机器人采用声通信或光通信。然而，前者带宽低，后者通信范围短。我们的策略通过受信息素启发的间接通信来协调水下机器人。间接通信是借助一组水下通信节点建立的。我们采用基于虚拟信息素的控制器，并提供了一组规则来将感兴趣区域整合到信息素中。基于虚拟信息素中的信息，制定了行为规律来指导蜂群进行监测和搜索，并利用附近的信息。此外，机器人可以利用额外的远距离信息素来提高其性能。通过采用自动调整访问周期的蜂群进化方案，进一步改进了监测策略。实验结果表明，我们的策略在大多数情况下优于随机策略。
