An architecture for adaptive task planning in support of IoT-based machine learning applications for disaster scenarios

The proliferation of the Internet of Things (IoT) in conjunction with edge computing has recently opened up several possibilities for several new applications. Typical examples are Unmanned Aerial Vehicles (UAV) that are deployed for rapid disaster response, photogrammetry, surveillance, and environmental monitoring. To support the flourishing development of Machine Learning assisted applications across all these networked applications, a common challenge is the provision of a persistent service, i.e., a service capable of consistently maintaining a high level of performance, facing possible failures. To address these service resilient challenges, we propose APRON, an edge solution for distributed and adaptive task planning management in a network of IoT devices, e.g., drones. Exploiting Jackson's network model, our architecture applies a novel planning strategy to better support control and monitoring operations while the states of the network evolve. To demonstrate the functionalities of our architecture, we also implemented a deep-learning based audio-recognition application using the APRON NorthBound interface, to detect human voices in challenged networks. The application's logic uses Transfer Learning to improve the audio classification accuracy and the runtime of the UAV-based rescue operations

Urban Air Mobility System Testbed Using CAVE Virtual Reality Environment

Urban Air Mobility (UAM) refers to a system of air passenger and small cargo transportation within an urban area. The UAM framework also includes other urban Unmanned Aerial Systems (UAS) services that will be supported by a mix of onboard, ground, piloted, and autonomous operations. Over the past few years UAM research has gained wide interest from companies and federal agencies as an on-demand innovative transportation option that can help reduce traffic congestion and pollution as well as increase mobility in metropolitan areas. The concepts of UAM/UAS operation in the National Airspace System (NAS) remains an active area of research to ensure safe and efficient operations. With new developments in smart vehicle design and infrastructure for air traffic management, there is a need for methods to integrate and test various components of the UAM framework. In this work, we report on the development of a virtual reality (VR) testbed using the Cave Automatic Virtual Environment (CAVE) technology for human-automation teaming and airspace operation research of UAM. Using a four-wall projection system with motion capture, the CAVE provides an immersive virtual environment with real-time full body tracking capability. We created a virtual environment consisting of San Francisco city and a vertical take-off-and-landing passenger aircraft that can fly between a downtown location and the San Francisco International Airport. The aircraft can be operated autonomously or manually by a single pilot who maneuvers the aircraft using a flight control joystick. The interior of the aircraft includes a virtual cockpit display with vehicle heading, location, and speed information. The system can record simulation events and flight data for post-processing. The system parameters are customizable for different flight scenarios; hence, the CAVE VR testbed provides a flexible method for development and evaluation of UAM framework

Key technologies for safe and autonomous drones

Drones/UAVs are able to perform air operations that are very difficult to be performed by manned aircrafts. In addition, drones' usage brings significant economic savings and environmental benefits, while reducing risks to human life. In this paper, we present key technologies that enable development of drone systems. The technologies are identified based on the usages of drones (driven by COMP4DRONES project use cases). These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. Also, we present the contributions of the COMP4DRONES project to improve existing technologies. These contributions aim to ease drones’ customization, and enable their safe operation.This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 826610. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Austria, Belgium, Czech Republic, France, Italy, Latvia, Netherlands. The total project budget is 28,590,748.75 EUR (excluding ESIF partners), while the requested grant is 7,983,731.61 EUR to ECSEL JU, and 8,874,523.84 EUR of National and ESIF Funding. The project has been started on 1st October 2019

Framework de planeamento de missões para frotas de drones interligados

The usage of aerial drones has become more popular as they also become more accessible, both in economic and usability terms. Nowadays, these vehicles can present reduced dimensions and a good cost-benefit ratio, which makes it possible for several services and applications supported by aerial drone networks to emerge. Some scenarios that benefit from the use of aerial drones are the monitoring of emergency situations and natural disasters, the patrolling of urban areas and support to police forces, and tourist applications such as the real-time video transmission of points of interest. It is common for the control of the drone to be dependent on human intervention in these situations, which requires professionals specialized in its control. However, in recent years, several solutions have emerged that enable the autonomous flight of these vehicles, minimizing manual interference. Taking into account the enormous diversity of use cases, many of the existing solutions for autonomous control focus on specific scenarios. Generic mission planning platforms also exist, but most of them only allow missions consisting of linear waypoints to be traversed. These situations translate into a mission support that is not very flexible. In this dissertation, we propose a modular infrastructure that can be used in various scenarios, enabling the autonomous control and monitoring of a fleet of aerial drones in a mission context. This platform has two main components, one integrated into the onboard computer of the vehicle, and the other one in the ground control. The former allows the communication with the flight controller so that it can collect telemetry data and send movement instructions to the drone. The latter allows to monitor this data and send the commands remotely, also enabling robust mission planning with multiple drones. A mission can be described in a script that the ground module interprets, sending the commands to the assigned vehicles. These missions can describe different paths, modifying the behaviour of the drones according to external factors, such as a sensor reading. It is also possible to define plugins to be reused in various missions, for example, by integrating an algorithm that ensures that all drones maintain connectivity. The solution was evaluated in scenarios with a single drone and with the collaboration of multiple drones. The tests were performed in a simulated environment and also in an environment with real drones. The observed behaviour is similar in both scenarios.A utilização de drones aéreos tem-se vindo a popularizar à medida que estes se tornam mais acessíveis, quer em termos económicos quer em usabilidade. Atualmente, estes veículos são capazes de apresentar dimensões reduzidas e uma boa relação de custo-benefício, o que potencia que diversos serviços e aplicações suportados por redes de drones aéreos estejam a emergir. Alguns cenários que beneficiam da utilização de drones aéreos são a monitorização de situações de emergência e catástrofes naturais, a patrulha de áreas urbanas e apoio às forças policiais e aplicações turísticas como a transmissão de vídeo em tempo real de pontos de interesse. É comum que o controlo do drone esteja dependente de intervenção humana nestas situações, o que requer profissionais especializados no seu controlo. No entanto, nos últimos anos têm surgido diversas soluções que possibilitam o vôo autónomo destes veículos, minimizando a interferência manual. Perante a enorme diversidade de casos de aplicação, muitas das soluções existentes para o controlo autónomo focam-se em cenários específicos de intervenção. Existem também plataformas de planeamento genérico de missões, mas que na sua maioria apenas permitem missões constituídas por conjuntos lineares de pontos a ser percorridos. Estas situações traduzem-se num suporte a missões que é pouco flexível. Nesta dissertação propomos uma infraestrutura modular passível de ser utilizada em cenários variados, possibilitando o controlo autónomo de uma frota de drones aéreos num contexto de missão e a sua monitorização. Esta plataforma tem dois componentes principais, um integrado no computador a bordo do veículo e o outro no controlo terrestre. O primeiro permite a comunicação com o controlador de vôo para que se possa recolher diversos dados de telemetria e enviar instruções de movimento para o drone. O segundo permite monitorizar esses dados e enviar os comandos remotamente, possibilitando também um planeamento robusto de missões com múltiplos drones. Uma missão pode ser descrita num script que o módulo terrestre interpreta, enviando os comandos para os veículos atribuídos. Estas missões podem descrever diversos caminhos, modificando o comportamento dos drones de acordo com factores externos, como a leitura de um sensor. Também é possível definir plugins para serem reutilizados em várias missões, como por exemplo, integrando um algoritmo que garante que todos os drones mantêm a conectividade. A solução foi avaliada em cenários com um único drone e com a colaboração de múltiplos drones. Os testes foram executados em ambiente simulado e também num ambiente com drones reais. O comportamento observado nas missões é semelhante em ambos os cenários.Mestrado em Engenharia de Computadores e Telemátic

Mobility on Demand in the United States

The growth of shared mobility services and enabling technologies, such as smartphone apps, is contributing to the commodification and aggregation of transportation services. This chapter reviews terms and definitions related to Mobility on Demand (MOD) and Mobility as a Service (MaaS), the mobility marketplace, stakeholders, and enablers. This chapter also reviews the U.S. Department of Transportation’s MOD Sandbox Program, including common opportunities and challenges, partnerships, and case studies for employing on-demand mobility pilots and programs. The chapter concludes with a discussion of vehicle automation and on-demand mobility including pilot projects and the potential transformative impacts of shared automated vehicles on parking, land use, and the built environment

Multi-Robot Systems: Challenges, Trends and Applications

This book is a printed edition of the Special Issue entitled “Multi-Robot Systems: Challenges, Trends, and Applications” that was published in Applied Sciences. This Special Issue collected seventeen high-quality papers that discuss the main challenges of multi-robot systems, present the trends to address these issues, and report various relevant applications. Some of the topics addressed by these papers are robot swarms, mission planning, robot teaming, machine learning, immersive technologies, search and rescue, and social robotics

REMOVED FROM THE COCKPIT: THE PILOT IDENTITY CRISIS AND THE RISE OF UNCREWED AIRCRAFT IN NAVAL AVIATION

In the transition from crewed to uncrewed aircraft, naval aviation has focused on the technical instead of the human aspects of the change. The transition challenges the traditional pilot identity, based on sitting in a cockpit and physically operating an aircraft, because pilots of uncrewed aircraft control them remotely or manage the battlefield rather than the cockpit. This thesis uses identity theory and social identity theory to analyze similar cultural factors in the Navy’s transition from sail-to-steam power in the 1800s to identify how and why some line officers resisted and rejected steam technology, inhibiting the transition. In this case study, naval leadership encouraged resistance through orders mandating sail over steam power and failed to direct the needed change in line officer identity when engineers took away propulsion control and replaced the symbols associated with the line officer identity. To avoid repeating this failure, the Navy must oversee the pilot identity transition in order to leverage the full potential of both technology and humans. Instead of creating division, naval leaders should emphasize unity by creating an inclusive pilot identity, using terms that do not focus on human occupants when referring to aircraft categories, and creating viable career paths for all.Outstanding ThesisEnsign, United States NavyApproved for public release. Distribution is unlimited