Importance and applications of robotic and autonomous systems (RAS) in railway maintenance sector: a review

Maintenance, which is critical for safe, reliable, quality, and cost-effective service, plays a dominant role in the railway industry. Therefore, this paper examines the importance and applications of Robotic and Autonomous Systems (RAS) in railway maintenance. More than 70 research publications, which are either in practice or under investigation describing RAS developments in the railway maintenance, are analysed. It has been found that the majority of RAS developed are for rolling-stock maintenance, followed by railway track maintenance. Further, it has been found that there is growing interest and demand for robotics and autonomous systems in the railway maintenance sector, which is largely due to the increased competition, rapid expansion and ever-increasing expense

Open-Source Drone Programming Course for Distance Engineering Education.

This article presents a full course for autonomous aerial robotics inside the RoboticsAcademy framework. This “drone programming” course is open-access and ready-to-use for any teacher/student to teach/learn drone programming with it for free. The students may program diverse drones on their computers without a physical presence in this course. Unmanned aerial vehicles (UAV) applications are essentially practical, as their intelligence resides in the software part. Therefore, the proposed course emphasizes drone programming through practical learning. It comprises a collection of exercises resembling drone applications in real life, such as following a road, visual landing, and people search and rescue, including their corresponding background theory. The course has been successfully taught for five years to students from several university engineering degrees. Some exercises from the course have also been validated in three aerial robotics competitions, including an international one. RoboticsAcademy is also briefly presented in the paper. It is an open framework for distance robotics learning in engineering degrees. It has been designed as a practical complement to the typical online videos of massive open online courses (MOOCs). Its educational contents are built upon robot operating system (ROS) middleware (de facto standard in robot programming), the powerful 3D Gazebo simulator, and the widely used Python programming language. Additionally, RoboticsAcademy is a suitable tool for gamified learning and online robotics competitions, as it includes several competitive exercises and automatic assessment toolspost-print5214 K

Approaching delivery as a service

This paper explores the new logistics business model of Delivery as a Service, a concept aiming at a more efficient, fast and customer-oriented practice, linking IT solution development, urban logistics operations, supply chain efficiency and new business models. Delivery as a Service (DaaS) is defined as a service-oriented delivery and business processes in line with customer expectations and needs in the on-demand economy. The approach of this paper is an industry report based on evidence collected in multiple exploratory European projects integrating ambitious and strategic findings on Internet of Things, urban planning, consolidation centres, transport optimisation, and clean vehicle use. It contributes to a future scenario of urban logistics business models

Artificial Intelligence, International Competition, and the Balance of Power (May 2018)

World leaders, CEOs, and academics have suggested that a revolution in artificial intelligence is upon us. Are they right, and what will advances in artificial intelligence mean for international competition and the balance of power? This article evaluates how developments in artificial intelligence (AI) — advanced, narrow applications in particular — are poised to influence military power and international politics. It describes how AI more closely resembles “enabling” technologies such as the combustion engine or electricity than a specific weapon. AI’s still-emerging developments make it harder to assess than many technological changes, especially since many of the organizational decisions about the adoption and uses of new technology that generally shape the impact of that technology are in their infancy. The article then explores the possibility that key drivers of AI development in the private sector could cause the rapid diffusion of military applications of AI, limiting first-mover advantages for innovators. Alternatively, given uncertainty about the technological trajectory of AI, it is also possible that military uses of AI will be harder to develop based on private-sector AI technologies than many expect, generating more potential first-mover advantages for existing powers such as China and the United States, as well as larger consequences for relative power if a country fails to adapt. Finally, the article discusses the extent to which U.S. military rhetoric about the importance of AI matches the reality of U.S. investments.LBJ School of Public Affair

Aerostack2: A Software Framework for Developing Multi-robot Aerial Systems

In recent years, the robotics community has witnessed the development of several software stacks for ground and articulated robots, such as Navigation2 and MoveIt. However, the same level of collaboration and standardization is yet to be achieved in the field of aerial robotics, where each research group has developed their own frameworks. This work presents Aerostack2, a framework for the development of autonomous aerial robotics systems that aims to address the lack of standardization and fragmentation of efforts in the field. Built on ROS 2 middleware and featuring an efficient modular software architecture and multi-robot orientation, Aerostack2 is a versatile and platform-independent environment that covers a wide range of robot capabilities for autonomous operation. Its major contributions include providing a logical level for specifying missions, reusing components and sub-systems for aerial robotics, and enabling the development of complete control architectures. All major contributions have been tested in simulation and real flights with multiple heterogeneous swarms. Aerostack2 is open source and community oriented, democratizing the access to its technology by autonomous drone systems developers

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