Target Tracking with a Flexible UAV Cluster Array

Unmanned aerial vehicle (UAV) cluster applications, for tasks such as target localisation and tracking, are required to collect and utilise the data received on “flexible” sensor arrays, where the sensors, i.e. UAVs in this scenario, have time-variant positions. In this paper, using a parametric channel model, a UAV cluster mobility model and a kinematic model of the targets, an extended Kalman based state space model is proposed that tracks the unknown UAV positions and target parameters snapshot by snapshot. Simulation studies illustrating the tracking capabilities of the proposed technique have been presented

Collaborative signal and information processing for target detection with heterogeneous sensor networks

In this paper, an approach for target detection and acquisition with heterogeneous sensor networks through strategic resource allocation and coordination is presented. Based on sensor management and collaborative signal and information processing, low-capacity low-cost sensors are strategically deployed to guide and cue scarce high performance sensors in the network to improve the data quality, with which the mission is eventually completed more efficiently with lower cost. We focus on the problem of designing such a network system in which issues of resource selection and allocation, system behaviour and capacity, target behaviour and patterns, the environment, and multiple constraints such as the cost must be addressed simultaneously. Simulation results offer significant insight into sensor selection and network operation, and demonstrate the great benefits introduced by guided search in an application of hunting down and capturing hostile vehicles on the battlefield

Al-Robotics team: A cooperative multi-unmanned aerial vehicle approach for the Mohamed Bin Zayed International Robotic Challenge

The Al-Robotics team was selected as one of the 25 finalist teams out of 143 applications received to participate in the first edition of the Mohamed Bin Zayed International Robotic Challenge (MBZIRC), held in 2017. In particular, one of the competition Challenges offered us the opportunity to develop a cooperative approach with multiple unmanned aerial vehicles (UAVs) searching, picking up, and dropping static and moving objects. This paper presents the approach that our team Al-Robotics followed to address that Challenge 3 of the MBZIRC. First, we overview the overall architecture of the system, with the different modules involved. Second, we describe the procedure that we followed to design the aerial platforms, as well as all their onboard components. Then, we explain the techniques that we used to develop the software functionalities of the system. Finally, we discuss our experimental results and the lessons that we learned before and during the competition. The cooperative approach was validated with fully autonomous missions in experiments previous to the actual competition. We also analyze the results that we obtained during the competition trials.Unión Europea H2020 73166

SNAP : A Software-Defined & Named-Data Oriented Publish-Subscribe Framework for Emerging Wireless Application Systems

The evolution of Cyber-Physical Systems (CPSs) has given rise to an emergent class of CPSs defined by ad-hoc wireless connectivity, mobility, and resource constraints in computation, memory, communications, and battery power. These systems are expected to fulfill essential roles in critical infrastructure sectors. Vehicular Ad-Hoc Network (VANET) and a swarm of Unmanned Aerial Vehicles (UAV swarm) are examples of such systems. The significant utility of these systems, coupled with their economic viability, is a crucial indicator of their anticipated growth in the future. Typically, the tasks assigned to these systems have strict Quality-of-Service (QoS) requirements and require sensing, perception, and analysis of a substantial amount of data. To fulfill these QoS requirements, the system requires network connectivity, data dissemination, and data analysis methods that can operate well within a system\u27s limitations. Traditional Internet protocols and methods for network connectivity and data dissemination are typically designed for well-engineering cyber systems and do not comprehensively support this new breed of emerging systems. The imminent growth of these CPSs presents an opportunity to develop broadly applicable methods that can meet the stated system requirements for a diverse range of systems and integrate these systems with the Internet. These methods could potentially be standardized to achieve interoperability among various systems of the future. This work presents a solution that can fulfill the communication and data dissemination requirements of a broad class of emergent CPSs. The two main contributions of this work are the Application System (APPSYS) system abstraction, and a complementary communications framework called the Software-Defined NAmed-data enabled Publish-Subscribe (SNAP) communication framework. An APPSYS is a new breed of Internet application representing the mobile and resource-constrained CPSs supporting data-intensive and QoS-sensitive safety-critical tasks, referred to as the APPSYS\u27s mission. The functioning of the APPSYS is closely aligned with the needs of the mission. The standard APPSYS architecture is distributed and partitions the system into multiple clusters where each cluster is a hierarchical sub-network. The SNAP communication framework within the APPSYS utilized principles of Information-Centric Networking (ICN) through the publish-subscribe communication paradigm. It further extends the role of brokers within the publish-subscribe paradigm to create a distributed software-defined control plane. The SNAP framework leverages the APPSYS design characteristics to provide flexible and robust communication and dynamic and distributed control-plane decision-making that successfully allows the APPSYS to meet the communication requirements of data-oriented and QoS-sensitive missions. In this work, we present the design, implementation, and performance evaluation of an APPSYS through an exemplar UAV swarm APPSYS. We evaluate the benefits offered by the APPSYS design and the SNAP communication framework in meeting the dynamically changed requirements of a data-intensive and QoS-sensitive Coordinated Search and Tracking (CSAT) mission operating in a UAV swarm APPSYS on the battlefield. Results from the performance evaluation demonstrate that the UAV swarm APPSYS successfully monitors and mitigates network impairment impacting a mission\u27s QoS to support the mission\u27s QoS requirements

Formation of a Wireless Communication System Based on a Swarm of Unmanned Aerial Vehicles

Проблематика. На даний час бурхливо розвивається новий напрямок в техніці рухомих систем, пов'язаний із застосуванням множини/групи рухомих багатофункціональних вузлів, які можуть створювати різні просторово-розподілені структури для різних застосувань: від розважальних шоу, до розвідувальної мережі. Йдеться про техніку малих безпілотних літальних апаратів(БЛА), частіше званих дронами, та їх використання в області побудови телекомунікаційних систем. Мета. Метою роботи є розробка основних принципів і стратегій для формування неоднорідної безпроводової системи зв'язку на базі рою безпілотних літаючих апаратів. Методи. Досліджуються структурно-функціональні методи побудови безпроводової мережі. Результати. Представлені сценарії централізованої і розподіленої побудови безпроводової мережі керування рою БЛА, проведена оцінка ускладнення функціональності вузлів рою в разі розподіленого сценарію. Розроблено схему поетапної реалізації життєвого циклу рою БЛА для послуг зв'язку. Представлений«молекулярний» сценарій просторової самоорганізації дронів-вузлів рою, який може бути реалізований за допомогою процедур«ланцюжка» і«спалаху». Запропоновано побудови деяких стратегій управління роєм: централізоване і децентралізоване з Ведучим, колективне само керування з обміном інформацією, децентралізоване керування з прогнозуванням, самоорганізація без обміну інформацією. Висновки. Розроблено основні принципи і стратегії формування неоднорідної безпроводової системи зв'язку на базі рою безпілотних літаючих апаратів. Розроблено стратегію колективного управління роєм дронів.Background. Currently, a new direction in the technology of mobile systems is rapidly developing, associated with the use of a set / group of mobile multifunctional elements that can create different spatially-distributed structures for various applications: from entertainment shows to intelligence networks. This is a technique of small unmanned aerial vehicles (UAV), often called drones, and their use in the field of building telecommunication systems. Objective. The aim of the work is to develop the basic principles and strategies for the formation of a heterogeneous wireless communication system based on a swarm of unmanned aerial vehicles. Methods. We study the structural and functional methods of building a wireless network. Results. Scenarios of centralized and distributed building of a wireless network of control of a swarm of UAVs are presented, assessment of the complexity of the functionality of swarm nodes inthe case of a distributed scenario is carried out. A schemeof phased implementation of the life cycle of a UAV swarm for communication services has been developed. The “molecular” scenario of spatial self-organization of the swarm-nodes of the swarm is presented, which can beimplemented using the “chain” and “flash” procedures. The proposed construction of some strategies for managing the swarm: centralized and decentralized with the Leader, collective self-management with information sharing,decentralized management withforecasting, self-organization without information sharing. Conclusions. The basic principles and strategies for the formation of a heterogeneous wireless communication system based on a swarm of unmanned aerial vehicles have been developed. A collective management strategy for a swarm of drones was developed. Keywords:swarm of unmanned aerial vehicles; drone swarm; communication system; life cycle; control network.Проблематика. В настоящее время очень бурно развивается новое направление в технике подвижных систем, связанное с применением множества/группы подвижных многофункциональных элементов, которые могут создавать различные пространственно-распределенные структуры для различных применений: от развлекательных шоу, до разведывательной сети. Речь идет о технике малых беспилотных летающих аппаратов(БЛА), чаще называемых дронами, и их использование в области построения телекоммуникационных систем. Цель. Целью работы является разработка основных принципов и стратегий для формирования неоднородной беспроводной системы связи на базе роя беспилотных летающих аппаратов. Методы. Исследуются структурно-функциональные методы построения беспроводной сети. Результаты. Представлены сценарии централизованного и распределенного построения беспроводной сети управления роя БЛА, проведена оценка усложнения функциональности узлов роя в случае распределенного сценария. Разработана схема поэтапной реализации жизненного цикла роя БЛА для услуг связи. Представлен«молекулярный» сценарий пространственной самоорганизации дронов-узлов роя, который может быть реализован посредством процедур

Distributed 3D-Beam Reforming for Hovering-Tolerant UAVs Communication over Coexistence: A Deep-Q Learning for Intelligent Space-Air-Ground Integrated Networks

In this paper, we present a novel distributed UAVs beam reforming approach to dynamically form and reform a space-selective beam path in addressing the coexistence with satellite and terrestrial communications. Despite the unique advantage to support wider coverage in UAV-enabled cellular communications, the challenges reside in the array responses' sensitivity to random rotational motion and the hovering nature of the UAVs. A model-free reinforcement learning (RL) based unified UAV beam selection and tracking approach is presented to effectively realize the dynamic distributed and collaborative beamforming. The combined impact of the UAVs' hovering and rotational motions is considered while addressing the impairment due to the interference from the orbiting satellites and neighboring networks. The main objectives of this work are two-fold: first, to acquire the channel awareness to uncover its impairments; second, to overcome the beam distortion to meet the quality of service (QoS) requirements. To overcome the impact of the interference and to maximize the beamforming gain, we define and apply a new optimal UAV selection algorithm based on the brute force criteria. Results demonstrate that the detrimental effects of the channel fading and the interference from the orbiting satellites and neighboring networks can be overcome using the proposed approach. Subsequently, an RL algorithm based on Deep Q-Network (DQN) is developed for real-time beam tracking. By augmenting the system with the impairments due to hovering and rotational motion, we show that the proposed DQN algorithm can reform the beam in real-time with negligible error. It is demonstrated that the proposed DQN algorithm attains an exceptional performance improvement. We show that it requires a few iterations only for fine-tuning its parameters without observing any plateaus irrespective of the hovering tolerance

Data fusion for unsupervised video object detection, tracking and geo-positioning

In this work we describe a system and propose a novel algorithm for moving object detection and tracking based on video feed. Apart of many well-known algorithms, it performs detection in unsupervised style, using velocity criteria for the objects detection. The algorithm utilises data from a single camera and Inertial Measurement Unit (IMU) sensors and performs fusion of video and sensory data captured from the UAV. The algorithm includes object tracking and detection, augmented by object geographical co-ordinates estimation. The algorithm can be generalised for any particular video sensor and is not restricted to any specific applications. For object tracking, Bayesian filter scheme combined with approximate inference is utilised. Object localisation in real-world co-ordinates is based on the tracking results and IMU sensor measurements

Detecting Invasive Insects Using Uncewed Aerial Vehicles and Variational Autoencoders

In this thesis, we use machine learning techniques to address limitations in our ability to monitor pest insect migrations. Invasive insect populations, such as the brown marmorated stink bug (BMSB), cause significant economic and environmental damages. In order to mitigate these damages, tracking BMSB migration is vital, but it also poses a challenge. The current state-of-the-art solution to track insect migrations is called mark-release-recapture. In mark-release-recapture, a researcher marks insects with a fluorescent powder, releases them back into the wild, and searches for the insects using ultra-violet flashlights at suspected migration destination locations. However, this involves a significant amount of labor and has a low recapture rate. By automating the insect search step, the recapture rate can be improved, reducing the amount of labor required in the process and improving the quality of the data. We propose a solution to the BMSB migration tracking problem using an unmanned aerial vehicle (UAV) to collect video data of the area of interest. Our system uses an ultra violet (UV) lighting array and digital cameras mounted on the bottom of the UAV, as well as artificial intelligence algorithms such as convolutional neural networks (CNN), and multiple hypotheses tracking (MHT) techniques. Specifically, we propose a novel computer vision method for insect detection using a Convolutional Variational Auto Encoder (CVAE). Our experimental results show that our system can detect BMSB with high precision and recall, outperforming the current state-of-the-art. Additionally, we associate insect observations using MHT, improving detection results and accurately counting real-world insects