Design of Ad Hoc Wireless Mesh Networks Formed by Unmanned Aerial Vehicles with Advanced Mechanical Automation

Ad hoc wireless mesh networks formed by unmanned aerial vehicles (UAVs) equipped with wireless transceivers (access points (APs)) are increasingly being touted as being able to provide a flexible "on-the-fly" communications infrastructure that can collect and transmit sensor data from sensors in remote, wilderness, or disaster-hit areas. Recent advances in the mechanical automation of UAVs have resulted in separable APs and replaceable batteries that can be carried by UAVs and placed at arbitrary locations in the field. These advanced mechanized UAV mesh networks pose interesting questions in terms of the design of the network architecture and the optimal UAV scheduling algorithms. This paper studies a range of network architectures that depend on the mechanized automation (AP separation and battery replacement) capabilities of UAVs and proposes heuristic UAV scheduling algorithms for each network architecture, which are benchmarked against optimal designs.Comment: 12 page

Adoption of vehicular ad hoc networking protocols by networked robots

This paper focuses on the utilization of wireless networking in the robotics domain. Many researchers have already equipped their robots with wireless communication capabilities, stimulated by the observation that multi-robot systems tend to have several advantages over their single-robot counterparts. Typically, this integration of wireless communication is tackled in a quite pragmatic manner, only a few authors presented novel Robotic Ad Hoc Network (RANET) protocols that were designed specifically with robotic use cases in mind. This is in sharp contrast with the domain of vehicular ad hoc networks (VANET). This observation is the starting point of this paper. If the results of previous efforts focusing on VANET protocols could be reused in the RANET domain, this could lead to rapid progress in the field of networked robots. To investigate this possibility, this paper provides a thorough overview of the related work in the domain of robotic and vehicular ad hoc networks. Based on this information, an exhaustive list of requirements is defined for both types. It is concluded that the most significant difference lies in the fact that VANET protocols are oriented towards low throughput messaging, while RANET protocols have to support high throughput media streaming as well. Although not always with equal importance, all other defined requirements are valid for both protocols. This leads to the conclusion that cross-fertilization between them is an appealing approach for future RANET research. To support such developments, this paper concludes with the definition of an appropriate working plan

Constructing Dynamic Ad-hoc Emergency Networks using Software-Defined Wireless Mesh Networks

Natural disasters and other emergency situations have the potential to destroy a whole network infrastructure needed for communication critical to emergency rescue, evacuation, and initial rehabilitation. Hence, the research community has begun to focus attention on rapid network reconstruction in such emergencies; however, research has tried to create or improve emergency response systems using traditional radio and satellite communications, which face high operation costs and frequent disruptions. This thesis proposes a centralized monitoring and control system to reconstruct ad-hoc networks in emergencies by using software-defined wireless mesh networks (SDWMN). The proposed framework utilizes wireless mesh networks and software-defined networking to provide real-time network monitoring services to restore Internet access in a targeted disaster zone. It dispatches mobile devices including unmanned aerial vehicles and self-driving cars to the most efficient location aggregation to recover impaired network connections by using a new GPS position finder (GPS-PF) algorithm. The algorithm is based on density-based spatial clustering that calculates the best position to deploy one of the mobile devices. The proposed system is evaluated using the common open research emulator to demonstrate its efficiency and high accessibility in emergency situations. The results obtained from the evaluation show that the performance of the emergency communication system is improved considerably with the incorporation of the framework

HIRO-NET.Heterogeneous intelligent robotic network for internet sharing in disaster scenarios

This article describes HIRO-NET, an Heterogeneous Intelligent Robotic Network. HIRO-NET is an emergency infrastructure-less network that aims to address the problem of providing connectivity in the immediate aftermath of a natural disaster, where no cellular or wide area network is operational and no Internet access is available. HIRO-NET establishes a two-tier wireless mesh network where the Lower Tier connects nearby survivors in a self-organized mesh via Bluetooth Low Energy (BLE) and the Upper Tier creates long-range VHF links between autonomous robots exploring the disaster stricken area. HIRO-NET’s main goal is to enable users in the disaster area to exchange text messages to share critical information and request help from first responders. The mesh network discovery problem is analyzed and a network protocol specifically designed to facilitate the exploration process is presented. We show how HIRO-NET robots successfully discover, bridge and interconnect local mesh networks. Results show that the Lower Tier always reaches network convergence and the Upper Tier can virtually extend HIRO-NET functionalities to the range of a small metropolitan area. In the event of an Internet connection still being available to some user, HIRO-NET is able to opportunistically share and provide access to low data-rate services (e.g., Twitter, Gmail) to the whole network. Results suggest that a temporary emergency network to cover a metropolitan area can be created in tens of minutes. Inde

Tactical Communications for Cooperative SAR Robot Missions

This chapter describes how the ICARUS communications (COM) team defined, developed and implemented an integrated wireless communication system to ensure an interoperable and dependable networking capability for both human and robotic search and rescue field teams and crisis managers. It starts explaining the analysis of the requirements and the context of the project, the existing solutions and the design of the ICARUS communication system to fulfil all the project needs. Next, it addresses the implementation process of the required networking capabilities, and finally, it explains how the ICARUS communication system and associated tools have been integrated in the overall mission systems and have been validated to provide reliable communications for real‐time information sharing during search and rescue operations in hostile conditions

Chapter Tactical Communications for Cooperative SAR Robot Missions

This chapter describes how the ICARUS communications (COM) team defined, developed and implemented an integrated wireless communication system to ensure an interoperable and dependable networking capability for both human and robotic search and rescue field teams and crisis managers. It starts explaining the analysis of the requirements and the context of the project, the existing solutions and the design of the ICARUS communication system to fulfil all the project needs. Next, it addresses the implementation process of the required networking capabilities, and finally, it explains how the ICARUS communication system and associated tools have been integrated in the overall mission systems and have been validated to provide reliable communications for real‐time information sharing during search and rescue operations in hostile conditions

Mission-based mobility models for UAV networks

Las redes UAV han atraído la atención de los investigadores durante la última década. Las numerosas posibilidades que ofrecen los sistemas single-UAV aumentan considerablemente al usar múltiples UAV. Sin embargo, el gran potencial del sistema multi-UAV viene con un precio: la complejidad de controlar todos los aspectos necesarios para garantizar que los UAVs cumplen la misión que se les ha asignado. Ha habido numerosas investigaciones dedicadas a los sistemas multi-UAV en el campo de la robótica en las cuales se han utilizado grupos de UAVs para diferentes aplicaciones. Sin embargo, los aspectos relacionados con la red que forman estos sistemas han comenzado a reclamar un lugar entre la comunidad de investigación y han hecho que las redes de UAVs se consideren como un nuevo paradigma entre las redes multi-salto. La investigación de redes de UAVs, de manera similar a otras redes multi-salto, se divide principalmente en dos categorías: i) modelos de movilidad que capturan la movilidad de la red, y ii) algoritmos de enrutamiento. Ambas categorías han heredado muchos algoritmos que pertenecían a las redes MANET, que fueron el primer paradigma de redes multi-salto que atrajo la atención de los investigadores. Aunque hay esfuerzos de investigación en curso que proponen soluciones para ambas categorías, el número de modelos de movilidad y algoritmos de enrutamiento específicos para redes UAV es limitado. Además, en el caso de los modelos de movilidad, las soluciones existentes propuestas son simplistas y apenas representan la movilidad real de un equipo de UAVs, los cuales se utilizan principalmente en operaciones orientadas a misiones, en la que cada UAV tiene asignados movimientos específicos. Esta tesis propone dos modelos de movilidad basados en misiones para una red de UAVs que realiza dos operaciones diferentes. El escenario elegido en el que se desarrollan las misiones corresponde con una región en la que ha ocurrido, por ejemplo, un desastre natural. La elección de este tipo de escenario se debe a que en zonas de desastre, la infraestructura de comunicaciones comúnmente está dañada o totalmente destruida. En este tipo de situaciones, una red de UAVs ofrece la posibilidad de desplegar rápidamente una red de comunicaciones. El primer modelo de movilidad, llamado dPSO-U, ha sido diseñado para capturar la movilidad de una red UAV en una misión con dos objetivos principales: i) explorar el área del escenario para descubrir las ubicaciones de los nodos terrestres, y ii) hacer que los UAVs converjan de manera autónoma a los grupos en los que se organizan los nodos terrestres (también conocidos como clusters). El modelo de movilidad dPSO-U se basa en el conocido algoritmo particle swarm optimization (PSO), considerando los UAV como las partículas del algoritmo, y también utilizando el concepto de valores dinámicos para la inercia, el local best y el neighbour best de manera que el modelo de movilidad tenga ambas capacidades: la de exploración y la de convergencia. El segundo modelo, denominado modelo de movilidad Jaccard-based, captura la movilidad de una red UAV que tiene asignada la misión de proporcionar servicios de comunicación inalámbrica en un escenario de mediano tamaño. En este modelo de movilidad se ha utilizado una combinación del virtual forces algorithm (VFA), de la distancia Jaccard entre cada par de UAVs y metaheurísticas como hill climbing y simulated annealing, para cumplir los dos objetivos de la misión: i) maximizar el número de nodos terrestres (víctimas) que se encuentran bajo el área de cobertura inalámbrica de la red UAV, y ii) mantener la red UAV como una red conectada, es decir, evitando las desconexiones entre UAV. Se han realizado simulaciones exhaustivas con herramientas software específicamente desarrolladas para los modelos de movilidad propuestos. También se ha definido un conjunto de métricas para cada modelo de movilidad. Estas métricas se han utilizado para validar la capacidad de los modelos de movilidad propuestos de emular los movimientos de una red UAV en cada misión.UAV networks have attracted the attention of the research community in the last decade. The numerous capabilities of single-UAV systems increase considerably by using multiple UAVs. The great potential of a multi-UAV system comes with a price though: the complexity of controlling all the aspects required to guarantee that the UAV team accomplish the mission that it has been assigned. There have been numerous research works devoted to multi-UAV systems in the field of robotics using UAV teams for different applications. However, the networking aspects of multi-UAV systems started to claim a place among the research community and have made UAV networks to be considered as a new paradigm among the multihop ad hoc networks. UAV networks research, in a similar manner to other multihop ad hoc networks, is mainly divided into two categories: i) mobility models that capture the network mobility, and ii) routing algorithms. Both categories have inherited previous algorithms mechanisms that originally belong to MANETs, being these the first multihop networking paradigm attracting the attention of researchers. Although there are ongoing research efforts proposing solutions for the aforementioned categories, the number of UAV networks-specific mobility models and routing algorithms is limited. In addition, in the case of the mobility models, the existing solutions proposed are simplistic and barely represent the real mobility of a UAV team, which are mainly used in missions-oriented operations. This thesis proposes two mission-based mobility models for a UAV network carrying out two different operations over a disaster-like scenario. The reason for selecting a disaster scenario is because, usually, the common communication infrastructure is malfunctioning or completely destroyed. In these cases, a UAV network allows building a support communication network which is rapidly deployed. The first mobility model, called dPSO-U, has been designed for capturing the mobility of a UAV network in a mission with two main objectives: i) exploring the scenario area for discovering the location of ground nodes, and ii) making the UAVs to autonomously converge to the groups in which the nodes are organized (also referred to as clusters). The dPSO-U mobility model is based on the well-known particle swarm optimization algorithm (PSO), considering the UAVs as the particles of the algorithm, and also using the concept of dynamic inertia, local best and neighbour best weights so the mobility model can have both abilities: exploration and convergence. The second one, called Jaccard-based mobility model, captures the mobility of a UAV network that has been assigned with the mission of providing wireless communication services in a medium-scale scenario. A combination of the virtual forces algorithm (VFA), the Jaccard distance between each pair of UAVs and metaheuristics such as hill climbing or simulated annealing have been used in this mobility model in order to meet the two mission objectives: i) to maximize the number of ground nodes (i.e. victims) under the UAV network wireless coverage area, and ii) to maintain the UAV network as a connected network, i.e. avoiding UAV disconnections. Extensive simulations have been performed with software tools that have been specifically developed for the proposed mobility models. Also, a set of metrics have been defined and measured for each mobility model. These metrics have been used for validating the ability of the proposed mobility models to emulate the movements of a UAV network in each mission