CSR: Small: Collaborative Research: Adaptive and Autonomous Energy Management on a Sensor Network Using Aerial Robots

这项研究引入了新的充电系统和算法来补充现有的系统，并导致在传感器网络上进行自主的、可持续的能量管理。桥梁故障检测等应用依赖于远离建筑物运行的传感器网络，通常缺乏长期监测的能量。在这些情况下，传统的充电方法(例如太阳能电池板)无法使用或不能提供足够的能量(例如在夜间)。为了实现这一目标，这项研究有三个关键组成部分。第一个组件开发了一种无线充电传感器节点的无人机(UAV)，一个基于磁场强度的定位系统，以及优化能量传输的自主控制算法。基于该系统，第二部分开发了多无人机系统中无人机轨迹优化的在线算法，以及在节点子集中导致能量不足的分布式算法，以实现有效的充电。最后，第三个组件提供模型和分布式算法来预测传感器节点未来的能量充值和使用情况。这项研究影响了一系列社会、教育和科学主题。该项目满足了国家通过自主、节能的传感器网络和机器人系统实现对桥梁完整性的定期监测的关键需求。考虑到老化的基础设施和有限的地方预算，通过当前的人工视觉检查过程来执行此类工作，改进桥梁故障检测是必要的。在教育方面，在K-12阶段，这提供了演示和讲习班，以加强现有的方案，鼓励年轻学生(特别是女性)攻读STEM领域。

This research introduces novel recharging systems and algorithms to supplement existing systems and lead to autonomous, sustainable energy management on sensor networks. Applications such as bridge fault detection that rely on sensor networks operating away from buildings often lack energy for long-term monitoring. In these scenarios traditional recharging methods (e.g. solar panels) are unavailable or cannot provide sufficient energy (e.g. at night). To achieve this, the research has three key components. The first component develops an unmanned aerial vehicle (UAV) to wirelessly recharge sensor nodes, a localization system based on magnetic field intensity, and autonomous control algorithms that optimize power transfer. Based on this system, the second part develops online algorithms for UAV trajectory optimization in systems with multiple UAVs as well as distributed algorithms that induce energy deficits in a subset of nodes to enable efficient recharging. Finally, the third component provides models and distributed algorithms to predict future energy recharging and usage for sensor nodes. This research impacts a range of societal, educational, and scientific topics. This project addresses a critical national need of enabling regular monitoring of bridge integrity through autonomous, energy efficient sensor network and robot systems. Improving bridge fault detection is necessary given aging infrastructure and limited local budgets for performing such work through current manual visual inspection processes. Educationally, at the K-12 level, this provides demos and workshops to enhance existing programs, encouraging young students (especially women) to pursue STEM fields.