Low-Cost UAV Swarm for Real-Time Object Detection Applications

With unmanned aerial vehicles (UAVs), also known as drones, becoming readily available and affordable, applications for these devices have grown immensely. One type of application is the use of drones to fly over large areas and detect desired entities. For example, a swarm of drones could detect marine creatures near the surface of the ocean and provide users the location and type of animal found. However, even with the reduction in cost of drone technology, such applications result costly due to the use of custom hardware with built-in advanced capabilities. Therefore, the focus of this thesis is to compile an easily customizable, low-cost drone design with the necessary hardware for autonomous behavior, swarm coordination, and on-board object detection capabilities. Additionally, this thesis outlines the necessary network architecture to handle the interconnection and bandwidth requirements of the drone swarm. The drone on-board system uses a PixHawk 4 flight controller to handle flight mechanics, a Raspberry Pi 4 as a companion computer for general-purpose computing power, and a NVIDIA Jetson Nano Developer Kit to perform object detection in real-time. The implemented network follows the 802.11s standard for multi-hop communications with the HWMP routing protocol. This topology allows drones to forward packets through the network, significantly extending the flight range of the swarm. Our experiments show that the selected hardware and implemented network can provide direct point-to-point communications at a range of up to 1000 feet, with extended range possible through message forwarding. The network also provides sufficient bandwidth for bandwidth intensive data such as live video streams. With an expected flight time of about 17 minutes, the proposed design offers a low-cost drone swarm solution for mid-range aerial surveillance applications

Modular event-driven unmanned aerial vehicles control platform

Hoje em dia, os drones estão-se a tornar cada vez mais comuns nas nossas vidas diárias. Com a agilidade, acessibilidade e diversidade dos drones, eles são uma excelente plataforma para transportar dispositivos (p.ex., conjunto de sensores, câmeras, unidades computacionais de pequena dimensão). Assim sendo, são uma excelente ferramenta para tarefas como: explorar e estudar áreas perigosas, monitorizar campos de agricultura, ajudar na detecção e combate de incêndios ou vigiar multidões. Para realizar tais tarefas, ferramentas de automação e integração são essenciais, para que o desenvolvimento se concentre na própria aplicação e não nos problemas relacionados com a integração e automação do sistema do drone. Os drones atualmente disponiveis não são capazes de lidar com tais complexidades de forma tão transparente. Por exemplo, certos niveis de automação são ja possiveis, mas requerem hardware e software especificos do fornecedor; no que toca a integração, alguns já supportam SDK ou API para interagir com o drone, mas mais uma vez com a inconveniência de necessitar de conhecimento prévio sobre os sistemas dos drones. Para responder a estas necessidades, esta tese propõe uma plataforma modular de controlo baseada em eventos para abstrair os processos de automação e integração da complexidade subjacentes aos drones. Enquanto que a plataforma permite que as aplicações controlem e interajam com os drones, a sua complexidade é resolvida dentro da plataforma, simplificando o processo de integração. Além disso, com a plataforma proposta, a automação e funcionalidades do drone podem ser estendidas para estender as funcionalidades de drones mais limitados. A plataforma desenvolvida foi testada em diferentes cenários, tanto ao nível das suas funcionalidades como ao nível da analise de desempenho. Os resultados mostram que, além das funcionalidades suportadas, a plataforma consegue suportar o controlo e gestão de pelo menos até 64 drones em simultâneo sem ter modificações significativas nos atrasos de comunicação e throughput.Nowadays, drones are becoming more common in our daily lives. Since drones are agile, a ordable and diverse, they make an excellent platform to carry devices around (e.g., sensor arrays, cameras, small computers). With these capabilities, they become an excellent tool for tasks like: explore and study hazardous areas, agriculture monitoring, help on the detection and ght in res, and crowd surveillance. To perform such tasks, automation and integration tools are a must have, so that the development can focus on the application itself and not on the issues related with the integration and automation of the drone system. Current available drones are not capable of properly handling such complexities in a seamless way. For instance, some levels of automation are already possible, but require vendor speci c hardware and software; for integration, some o er SDK or API interactions, but once again with the inconvenience of requiring extensive knowledge about drone systems to implement. To address these issues, this thesis proposes a modular event-driven control platform to abstract automation and integration processes from the underlying complexities of the drones, while the platform lets the applications control and interact with the drones. The drones' complexities are resolved within the platform, therefore simplifying integration process. Moreover, with the proposed platform, drone automation and functionality can be extended across distinct brands of drones, while some may already support some features, others may not, and in that case the platform modules may intervene to extend the features of less capable drones. The developed platform has been tested in di erent scenarios, such as in terms of its functionalities and in terms of performance analysis. The results show that, besides the supported functionalities, the platform is able to handle the control and management of at last 64 simultaneous drones without signi cant changes in the communication delays and throughput.Mestrado em Engenharia Informátic

Development of a drone-based miniaturized Flexible Microwave Payload (FMPL) for GNSS-Reflectometry and L-band radiometry

This project has been developed in collaboration with the NanosatLab UPC, which develops CubeSats for educational and scientific purposes and in-orbit technology demonstration. More specifically, the laboratory is focused on remote sensing systems. In recent years, the NanosatLab UPC has been developing the Flexible Microwave PayLoad (FMPL), the integration of different microwave remote sensing equipment in a single system: reflectometry Global Navigation Satellite System (GNSS) signals (GNSS-R) and microwave radiometry (MWR) in L-band. In 2022, the second version of this system, FMPL-2, is in orbit on board the CubeSat 3Cat5, which has provided precious scientific data on the climate of the earth and the evolution of climate change. The first version, FMPL-1, will be launched in the coming months aboard CubeSat 3Cat4. The third version, FMPL-3, is now ready for launch on board the CubeSat GNSSaS. From space, FMPL has proven to be a very useful tool for studying climate change. This work aims to design, build and test the first FMPL for drones, the FMPL-D. This new platform will be used to evaluate new versions of FMPL. It will also be a valuable tool to study the characteristics of soil, water, ice and vegetation locally and with a spatial resolution much greater than that which can be obtained from a satellite. The results presented in this thesis put the complexity of these systems into perspective. Firstly, in the results of the radiometer, an effect of distortion and destruction of the data obtained due to the radio frequency interference received during the measurement campaigns has been observed, highlighting the need for detection and mitigation systems interference for ground observation missions. For the GNSS reflectometry instrument, multiple flights were conducted in which large amounts of data were collected, the processing of which is still in progress. Preliminary results indicate good characteristics of the radio frequency chain. This Final Degree Project (TFG) is the first version of the FMPL-D, culminating in the system's first version and many lessons learned.Objectius de Desenvolupament Sostenible::13 - Acció per al Clim

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Acknowledgments We thank Johan Havelaar, Aeryon Labs Inc., AeronVironment Inc. and Aeronautics Inc. for kindly permitting the use of materials in Fig. 1.Peer reviewedPublisher PD

Localization and detection of wireless embeddable structural sensors using an unmanned aerial vehicle in the absence of visual markers

The objective of this thesis is to develop a fully integrated UAV based platform for autonomous collection of data from embedded sensors. Passive (battery-less) embedded sensors provide means for periodic long-term monitoring of civil structures like bridges. However, collection of data from these sensors requires extensive manual effort of locating them. UAVs can automate this process, although localization of these embedded tags in absence of visual markers pose a challenge. A RF (13.56MHz) reader is used to capture data from RF tags wirelessly. Different tag coil sizes are tested to observe effects on read range as well as to characterize the interaction volume between reader and tag. The UAV platform is integrated with the RF reader to autonomously capture data from tags using GPS based localization. Different sensor configurations are tested and characterized to meet the requirements of X,Y,Z localization set by the reader and tag interaction volume. Flight characteristics are also observed for various UAV navigation parameters. Results suggest that by using low-cost RTK GPS unit, the UAV is capable of detecting and localizing RF tags without any visual markers or aides.Electrical and Computer Engineerin

Introducing autonomous aerial robots in industrial manufacturing

Although ground robots have been successfully used for many years in manufacturing, the capability of aerial robots to agilely navigate in the often sparse and static upper part of factories makes them suitable for performing tasks of interest in many industrial sectors. This paper presents the design, development, and validation of a fully autonomous aerial robotic system for manufacturing industries. It includes modules for accurate pose estimation without using a Global Navigation Satellite System (GNSS), autonomous navigation, radio-based localization, and obstacle avoidance, among others, providing a fully onboard solution capable of autonomously performing complex tasks in dynamic indoor environments in which all necessary sensors, electronics, and processing are on the robot. It was developed to fulfill two use cases relevant in many industries: light object logistics and missing tool search. The presented robotic system, functionalities, and use cases have been extensively validated with Technology Readiness Level 7 (TRL-7) in the Centro Bahía de C´ adiz (CBC) Airbus D&S factory in fully working conditions.Comisión Europea 60884Horizonte 2020 (Unión Europea) 871479Plan Nacional de I+D+I DPI2017-8979-

Can Urban Air Mobility become reality? Opportunities, challenges and selected research results

Urban Air Mobility (UAM) is a new air transportation system for passengers and cargo in urban environments, enabled by new technologies and integrated into multimodal transportation systems. The vision of UAM comprises the mass use in urban and suburban environments, complementing existing transportation systems and contributing to the decarbonization of the transport sector. Initial attempts to create a market for urban air transportation in the last century failed due to lack of profitability and community acceptance. Technological advances in numerous fields over the past few decades have led to a renewed interest in urban air transportation. UAM is expected to benefit users and to also have a positive impact on the economy by creating new markets and employment opportunities for manufacturing and operation of UAM vehicles and the construction of related ground infrastructure. However, there are also concerns about noise, safety and security, privacy and environmental impacts. Therefore, the UAM system needs to be designed carefully to become safe, affordable, accessible, environmentally friendly, economically viable and thus sustainable. This paper provides an overview of selected key research topics related to UAM and how the German Aerospace Center (DLR) contributed to this research in the project "HorizonUAM - Urban Air Mobility Research at the German Aerospace Center (DLR)". Selected research results that support the realization of the UAM vision are briefly presented.Comment: 20 pages, 7 figures, project HorizonUA

A multi-purpose, multi-rotor drone system for long-range and high-altitude volcanic gas plume measurements

A multi-rotor drone has been adapted for studies of volcanic gas plumes. This adaptation includes improved capacity for high-altitude and long-range, real-time SO2 concentration monitoring, long-range manual control, remotely activated bag sampling and plume speed measurement capability. The drone is capable of acting as a stable platform for various instrument configurations, including multi-component gas analysis system (MultiGAS) instruments for in situ measurements of SO2, H2S, and CO2 concentrations in the gas plume and portable differential optical absorption spectrometer (MobileDOAS) instruments for spectroscopic measurement of total SO2 emission rate, remotely controlled gas sampling in bags and sampling with gas denuders for posterior analysis on the ground of isotopic composition and halogens. The platform we present was field-tested during three campaigns in Papua New Guinea: in 2016 at Tavurvur, Bagana and Ulawun volcanoes, in 2018 at Tavurvur and Langila volcanoes and in 2019 at Tavurvur and Manam volcanoes, as well as in Mt. Etna in Italy in 2017. This paper describes the drone platform and the multiple payloads, the various measurement strategies and an algorithm to correct for different response times of MultiGAS sensors. Specifically, we emphasize the need for an adaptive flight path, together with live data transmission of a plume tracer (such as SO2 concentration) to the ground station, to ensure optimal plume interception when operating beyond the visual line of sight. We present results from a comprehensive plume characterization obtained during a field deployment at Manam volcano in May 2019. The Papua New Guinea region, and particularly Manam volcano, has not been extensively studied for volcanic gases due to its remote location, inaccessible summit region and high level of volcanic activity. We demonstrate that the combination of a multi-rotor drone with modular payloads is a versatile solution to obtain the flux and composition of volcanic plumes, even for the case of a highly active volcano with a high-altitude plume such as Manam. Drone-based measurements offer a valuable solution to volcano research and monitoring applications and provide an alternativespan idCombining double low line"page4256"/> and complementary method to ground-based and direct sampling of volcanic gases