Multi-UAV Integrated Internet of Things System for Generating Safe Map in Post-Disaster

芝浦工業大学2019年

Aerial Network Assistance Systems for Post-Disaster Scenarios : Topology Monitoring and Communication Support in Infrastructure-Independent Networks

Communication anytime and anywhere is necessary for our modern society to function. However, the critical network infrastructure quickly fails in the face of a disaster and leaves the affected population without means of communication. This lack can be overcome by smartphone-based emergency communication systems, based on infrastructure-independent networks like Delay-Tolerant Networks (DTNs). DTNs, however, suffer from short device-to-device link distances and, thus, require multi-hop routing or data ferries between disjunct parts of the network. In disaster scenarios, this fragmentation is particularly severe because of the highly clustered human mobility behavior. Nevertheless, aerial communication support systems can connect local network clusters by utilizing Unmanned Aerial Vehicles (UAVs) as data ferries. To facilitate situation-aware and adaptive communication support, knowledge of the network topology, the identification of missing communication links, and the constant reassessment of dynamic disasters are required. These requirements are usually neglected, despite existing approaches to aerial monitoring systems capable of detecting devices and networks. In this dissertation, we, therefore, facilitate the coexistence of aerial topology monitoring and communications support mechanisms in an autonomous Aerial Network Assistance System for infrastructure-independent networks as our first contribution. To enable system adaptations to unknown and dynamic disaster situations, our second contribution addresses the collection, processing, and utilization of topology information. For one thing, we introduce cooperative monitoring approaches to include the DTN in the monitoring process. Furthermore, we apply novel approaches for data aggregation and network cluster estimation to facilitate the continuous assessment of topology information and an appropriate system adaptation. Based on this, we introduce an adaptive topology-aware routing approach to reroute UAVs and increase the coverage of disconnected nodes outside clusters. We generalize our contributions by integrating them into a simulation framework, creating an evaluation platform for autonomous aerial systems as our third contribution. We further increase the expressiveness of our aerial system evaluation, by adding movement models for multicopter aircraft combined with power consumption models based on real-world measurements. Additionally, we improve the disaster simulation by generalizing civilian disaster mobility based on a real-world field test. With a prototypical system implementation, we extensively evaluate our contributions and show the significant benefits of cooperative monitoring and topology-aware routing, respectively. We highlight the importance of continuous and integrated topology monitoring for aerial communications support and demonstrate its necessity for an adaptive and long-term disaster deployment. In conclusion, the contributions of this dissertation enable the usage of autonomous Aerial Network Assistance Systems and their adaptability in dynamic disaster scenarios

Advances in integrating autonomy with acoustic communications for intelligent networks of marine robots

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2013Autonomous marine vehicles are increasingly used in clusters for an array of oceanographic tasks. The effectiveness of this collaboration is often limited by communications: throughput, latency, and ease of reconfiguration. This thesis argues that improved communication on intelligent marine robotic agents can be gained from acting on knowledge gained by improved awareness of the physical acoustic link and higher network layers by the AUV’s decision making software. This thesis presents a modular acoustic networking framework, realized through a C++ library called goby-acomms, to provide collaborating underwater vehicles with an efficient short-range single-hop network. goby-acomms is comprised of four components that provide: 1) losslessly compressed encoding of short messages; 2) a set of message queues that dynamically prioritize messages based both on overall importance and time sensitivity; 3) Time Division Multiple Access (TDMA) Medium Access Control (MAC) with automatic discovery; and 4) an abstract acoustic modem driver. Building on this networking framework, two approaches that use the vehicle’s “intelligence” to improve communications are presented. The first is a “non-disruptive” approach which is a novel technique for using state observers in conjunction with an entropy source encoder to enable highly compressed telemetry of autonomous underwater vehicle (AUV) position vectors. This system was analyzed on experimental data and implemented on a fielded vehicle. Using an adaptive probability distribution in combination with either of two state observer models, greater than 90% compression, relative to a 32-bit integer baseline, was achieved. The second approach is “disruptive,” as it changes the vehicle’s course to effect an improvement in the communications channel. A hybrid data- and model-based autonomous environmental adaptation framework is presented which allows autonomous underwater vehicles (AUVs) with acoustic sensors to follow a path which optimizes their ability to maintain connectivity with an acoustic contact for optimal sensing or communication.I wish to acknowledge the sponsors of this research for their generous support of my tuition, stipend, and research: the WHOI/MIT Joint Program, the MIT Presidential Fellowship, the Office of Naval Research (ONR) # N00014-08-1-0011, # N00014-08-1-0013, and the ONR PlusNet Program Graduate Fellowship, the Defense Advanced Research Projects Agency (DARPA) (Deep Sea Operations: Applied Physical Sciences (APS) Award # APS 11-15 3352-006, APS 11-15-3352-215 ST 2.6 and 2.7

Collaboratively Navigating Autonomous Systems

The objective of this project is to focus on technologies for enabling heterogeneous networks of autonomous vehicles to cooperate together on a specific task. The prototyped test bed consists of a retrofitted electric golf cart and a quadrotor designed to perform distributed information gathering to guide decision making across the entire test bed. The system prototype demonstrates several aspects of this technology and lays the groundwork for future projects in this area

A Survey on Energy Optimization Techniques in UAV-Based Cellular Networks: From Conventional to Machine Learning Approaches

Wireless communication networks have been witnessing an unprecedented demand due to the increasing number of connected devices and emerging bandwidth-hungry applications. Albeit many competent technologies for capacity enhancement purposes, such as millimeter wave communications and network densification, there is still room and need for further capacity enhancement in wireless communication networks, especially for the cases of unusual people gatherings, such as sport competitions, musical concerts, etc. Unmanned aerial vehicles (UAVs) have been identified as one of the promising options to enhance the capacity due to their easy implementation, pop up fashion operation, and cost-effective nature. The main idea is to deploy base stations on UAVs and operate them as flying base stations, thereby bringing additional capacity to where it is needed. However, because the UAVs mostly have limited energy storage, their energy consumption must be optimized to increase flight time. In this survey, we investigate different energy optimization techniques with a top-level classification in terms of the optimization algorithm employed; conventional and machine learning (ML). Such classification helps understand the state of the art and the current trend in terms of methodology. In this regard, various optimization techniques are identified from the related literature, and they are presented under the above mentioned classes of employed optimization methods. In addition, for the purpose of completeness, we include a brief tutorial on the optimization methods and power supply and charging mechanisms of UAVs. Moreover, novel concepts, such as reflective intelligent surfaces and landing spot optimization, are also covered to capture the latest trend in the literature.Comment: 41 pages, 5 Figures, 6 Tables. Submitted to Open Journal of Communications Society (OJ-COMS