Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

Aquatic escape for micro-aerial vehicles

As our world is experiencing climate changes, we are in need of better monitoring technologies. Most of our planet is covered with water and robots will need to move in aquatic environments. A mobile robotic platform that possesses efficient locomotion and is capable of operating in diverse scenarios would give us an advantage in data collection that can validate climate models, emergency relief and experimental biological research. This field of application is the driving vector of this robotics research which aims to understand, produce and demonstrate solutions of aerial-aquatic autonomous vehicles. However, small robots face major challenges in operating both in water and in air, as well as transition between those fluids, mainly due to the difference of density of the media. This thesis presents the developments of new aquatic locomotion strategies at small scales that further enlarge the operational domain of conventional platforms. This comprises flight, shallow water locomotion and the transition in-between. Their operating principles, manufacturing methods and control methods are discussed and evaluated in detail. I present multiple unique aerial-aquatic robots with various water escape mechanisms, spanning over different scales. The five robotic platforms showcased share similarities that are compared. The take-off methods are analysed carefully and the underlying physics principles put into light. While all presented research fulfils a similar locomotion objective - i.e aerial and aquatic motion - their relevance depends on the environmental conditions and supposed mission. As such, the performance of each vehicle is discussed and characterised in real, relevant conditions. A novel water-reactive fuel thruster is developed for impulsive take-off, allowing consecutive and multiple jump-gliding from the water surface in rough conditions. At a smaller scale, the escape of a milligram robotic bee is achieved. In addition, a new robot class is demonstrated, that employs the same wings for flying as for passive surface sailing. This unique capability allows the flexibility of flight to be combined with long-duration surface missions, enabling autonomous prolonged aquatic monitoring.Open Acces

Probabilistic Human-Robot Information Fusion

This thesis is concerned with combining the perceptual abilities of mobile robots and human operators to execute tasks cooperatively. It is generally agreed that a synergy of human and robotic skills offers an opportunity to enhance the capabilities of today’s robotic systems, while also increasing their robustness and reliability. Systems which incorporate both human and robotic information sources have the potential to build complex world models, essential for both automated and human decision making. In this work, humans and robots are regarded as equal team members who interact and communicate on a peer-to-peer basis. Human-robot communication is addressed using probabilistic representations common in robotics. While communication can in general be bidirectional, this work focuses primarily on human-to-robot information flow. More specifically, the approach advocated in this thesis is to let robots fuse their sensor observations with observations obtained from human operators. While robotic perception is well-suited for lower level world descriptions such as geometric properties, humans are able to contribute perceptual information on higher abstraction levels. Human input is translated into the machine representation via Human Sensor Models. A common mathematical framework for humans and robots reinforces the notion of true peer-to-peer interaction. Human-robot information fusion is demonstrated in two application domains: (1) scalable information gathering, and (2) cooperative decision making. Scalable information gathering is experimentally demonstrated on a system comprised of a ground vehicle, an unmanned air vehicle, and two human operators in a natural environment. Information from humans and robots was fused in a fully decentralised manner to build a shared environment representation on multiple abstraction levels. Results are presented in the form of information exchange patterns, qualitatively demonstrating the benefits of human-robot information fusion. The second application domain adds decision making to the human-robot task. Rational decisions are made based on the robots’ current beliefs which are generated by fusing human and robotic observations. Since humans are considered a valuable resource in this context, operators are only queried for input when the expected benefit of an observation exceeds the cost of obtaining it. The system can be seen as adjusting its autonomy at run-time based on the uncertainty in the robots’ beliefs. A navigation task is used to demonstrate the adjustable autonomy system experimentally. Results from two experiments are reported: a quantitative evaluation of human-robot team effectiveness, and a user study to compare the system to classical teleoperation. Results show the superiority of the system with respect to performance, operator workload, and usability

Cognitive Hyperconnected Digital Transformation

Cognitive Hyperconnected Digital Transformation provides an overview of the current Internet of Things (IoT) landscape, ranging from research, innovation and development priorities to enabling technologies in a global context. It is intended as a standalone book in a series that covers the Internet of Things activities of the IERC-Internet of Things European Research Cluster, including both research and technological innovation, validation and deployment. The book builds on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT-EPI) and the IoT European Large-Scale Pilots Programme, presenting global views and state-of-the-art results regarding the challenges facing IoT research, innovation, development and deployment in the next years. Hyperconnected environments integrating industrial/business/consumer IoT technologies and applications require new IoT open systems architectures integrated with network architecture (a knowledge-centric network for IoT), IoT system design and open, horizontal and interoperable platforms managing things that are digital, automated and connected and that function in real-time with remote access and control based on Internet-enabled tools. The IoT is bridging the physical world with the virtual world by combining augmented reality (AR), virtual reality (VR), machine learning and artificial intelligence (AI) to support the physical-digital integrations in the Internet of mobile things based on sensors/actuators, communication, analytics technologies, cyber-physical systems, software, cognitive systems and IoT platforms with multiple functionalities. These IoT systems have the potential to understand, learn, predict, adapt and operate autonomously. They can change future behaviour, while the combination of extensive parallel processing power, advanced algorithms and data sets feed the cognitive algorithms that allow the IoT systems to develop new services and propose new solutions. IoT technologies are moving into the industrial space and enhancing traditional industrial platforms with solutions that break free of device-, operating system- and protocol-dependency. Secure edge computing solutions replace local networks, web services replace software, and devices with networked programmable logic controllers (NPLCs) based on Internet protocols replace devices that use proprietary protocols. Information captured by edge devices on the factory floor is secure and accessible from any location in real time, opening the communication gateway both vertically (connecting machines across the factory and enabling the instant availability of data to stakeholders within operational silos) and horizontally (with one framework for the entire supply chain, across departments, business units, global factory locations and other markets). End-to-end security and privacy solutions in IoT space require agile, context-aware and scalable components with mechanisms that are both fluid and adaptive. The convergence of IT (information technology) and OT (operational technology) makes security and privacy by default a new important element where security is addressed at the architecture level, across applications and domains, using multi-layered distributed security measures. Blockchain is transforming industry operating models by adding trust to untrusted environments, providing distributed security mechanisms and transparent access to the information in the chain. Digital technology platforms are evolving, with IoT platforms integrating complex information systems, customer experience, analytics and intelligence to enable new capabilities and business models for digital business

A Framework for Learning by Demonstration in Multi-teacher Multi-robot Scenarios

As robots become more accessible to humans, more intuitive and human-friendly ways of programming them with interactive and group-aware behaviours are needed. This thesis addresses the gap between Learning by Demonstration and Multi-robot systems. In particular, this thesis tackles the fundamental problem of learning multi-robot cooperative behaviour from concurrent multi-teacher demonstrations, problem which had not been addressed prior to this work. The core contribution of this thesis is the design and implementation of a novel, multi- layered framework for multi-robot learning from simultaneous demonstrations, capable of deriving control policies at two different levels of abstraction. The lower level learns models of joint-actions at trajectory level, adapting such models to new scenarios via feature mapping. The higher level extracts the structure of cooperative tasks at symbolic level, generating a sequence of robot actions composing multi-robot plans. To the best of the author's knowledge, the proposed framework is the first Learning by Demonstration system to enable multiple human demonstrators to simultaneously teach group behaviour to multiple robots learners. A series of experimental tests were conducted using real robots in a real human workspace environment. The results obtained from a comprehensive comparison confirm the appli- cability of the joint-action model adaptation method utilised. What is more, the results of several trials provide evidence that the proposed framework effectively extracts rea- sonable multi-robot plans from demonstrations. In addition, a case study of the impact of human communication when using the proposed framework was conducted, suggesting no evidence that communication affects the time to completion of a task, but may have a positive effect on the extraction multi-robot plans. Furthermore, a multifaceted user study was conducted to analyse the aspects of user workload and focus of attention, as well as to evaluate the usability of the teleoperation system, highlighting which parts were necessary to be improved

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

Nonlinear Control Strategies for Outdoor Aerial Manipulators

In this thesis, the design, validation and implementation of nonlinear control strategies for aerial manipulators {i.e. aerial robots equipped with manipulators{ is studied, with special emphasis on the internal coupling of the system and its resilience against external disturbances. For the rst, di erent decentralised control strategies {i.e. using di erent control typologies for each one of the subsystems{ that indirectly take into account this coupling have been analysed. As a result, a nonlinear strategy composed of two controllers is proposed. A higher priority is given to the manipulation accuracy, relaxing the platform tracking, and hence obtaining a solution improving the manipulation capabilities with the surrounding environment. To validate these results, thorough stability and robustness analyses are provided, both theoretically and in simulation. On the other hand, a signi cant e ort has been devoted to improving the response and applicability of robot manipulators used in ight via control. In particular, the design of controllers for lightweight exible manipulators {that reduce the consequences of incidents involving unforeseen contacts{ is analysed. Although their inherent nature perfectly ts for aerial manipulation applications, the added exibility produces unwanted behaviours, such as second-order modes and uncertainties. To cope with them, an adaptable position nonlinear control strategy is proposed. To validate this contribution, the stability of the approach is studied in theory and its capabilities are proven in several experimental scenarios. In these, the robustness of the solution against unforeseen impacts and contact with uncharacterised interfaces is demonstrated. Subsequently, this strategy has been enriched with {multiaxis{ force control capabilities thanks to the inclusion of an outer control loop modifying the manipulator reference. Accordingly, this additional applicationfocused capability is added to the controlled system without loosing the modulated response of the inner-loop position strategy. It is also worth noting that, thanks to the cascade-like nature of the modi cation, the transition between position and force control modes is inherently smooth and automatic. The stability of this expanded strategy has been theoretically analysed and the results validated in a set of experimental scenarios. To validate the rst nonlinear approach with realistic outdoor simulations before its implementation, a computational uid dynamics analysis has been performed to obtain an explicit model of the aerodynamic forces and torques applied to the blunt-body of the aerial platform in ight. The results of this study have been compared to the most common alternative nowadays, being highlighted that the proposed model signi cantly surpasses this option in terms of accuracy. Moreover, it is worth underscoring that this characterisation could be also employed in the future to develop control solutions with enhanced rejection capabilities against wind conditions. Finally, as the focus of this thesis is on the use of novel control strategies on real aerial manipulation outdoors to improve their accuracy while performing complex tasks, a modular autopilot solution to be able to implement them has been also developed. This general-purpose autopilot allows the implementation of new algorithms, and facilitates their theory-to-experimentation transition. Taking into account this perspective, the proposed tool employs the simple and widely-known MAS interface and the highly reliable PX4 autopilot as backup, thus providing a redundant approach to handle unexpected incidents in ight.En esta tesis se ha estudiado el diseño, validación e implementación de estrategias de control no lineales para robots manipuladores aéreos –esto es, robots aéreos equipados con un sistema de manipulación robótica–, dándose especial énfasis a las interacciones internas del sistema y a su resiliencia frente a efectos externos. Para lo primero, se han analizado diferentes estrategias de control descentralizado –es decir, que usan tipologías de control diferentes para cada uno de los subsistemas–, pero que tienen indirectamente en consideración la interacción entre manipulación y vuelo. Como resultado de esta línea, se propone una estretegia de control conformada por dos controladores. Estos se coordinan de tal forma que se le da prioridad a la manipulación sobre el seguimiento de posiciones del vehículo, produciéndose un sistema de control que mejora la precisión de las interacciones entre el sistema manipulador y el entorno. Para validar estos resultados, se ha analizado su estabilidad y robustez tanto teóricamente como mediante simulaciones numéricas. Por otro lado, se ha buscado mejorar la respuesta y aplicabilidad de los manipuladores que se usan en vuelo mediante su control. Dentro de esta tendencia, la tesis se ha centrado en el diseño de controladores para manipuladores ligeros flexibles, ya que estos permiten reducir el peso del sistema completo y reducen el riesgo de incidentes debidos a contactos inesperados. Sin embargo, la flexibilidad de estos produce comportamientos indeseados durante la operación, como la aparición de modos de segundo orden y cierta incentidumbre en su comportamiento. Para reducir su impacto en la precisión de las tareas de manipulación, se ha desarrollado un controlador no lineal adaptable. Para validar estos resultados, se ha analizado la estabilidad del sistema teóricamente y se han desarrollado una serie de experimentos. En ellos, se ha comprobado su robustez ante impactos inesperados y contactos con elementos no caracterizados. Posteriormente, esta estrategia para manipuladores flexibles ha sido ampliada al añadir un bucle externo que posibilita el control en fuerzas en varias direcciones. Esto permite, mediante un único controlador, mantener la suave respuesta de la estrategia. Además cabe destacar que, al contar esta estrategia con un diseño en cascade, la transición entre los segmentos de desplazamiento del brazo y de aplicación de fuerzas es fluida y automática. La estabilidad de esta estrategia ampliada ha sido analizada teóricamente y los resultados han sido validados experimentalmente. Para validar la primera estrategia mediante simulaciones que representen fielmente las condiciones en exteriores antes de su implementación, ha sido necesario realizar un estudio mediante mecánica de fluidos computacional para obtener un modelo explícito de las fuerzas y momentos aerodinámicos a los que se efrenta la plataforma en vuelo. Los resultados de este estudio han sido comparados con la alternativa más empleada actualmente, mostrándose que los avances del método propuesto son sustanciales. Asimismo, es importante destacar que esta caracterización podría también usarse en el futuro para desarrollar controladores con una respuesta mejorada ante perturbaciones aerodinámicas, como en el caso de volar con viento. Finalmente, al ser esta una tesis centrada en las estrategias de control novedosas en sistemas reales para la mejora de su rendimiento en misiones complejas, se ha desarrollado un autopiloto modular fácilmente modificable para implementarlas. Este permite validar experimentalmente nuevos algoritmos y facilita la transición entre teoría y práctica. Para ello, esta herramienta se basa en una interfaz sencilla ampliamente conocida por los investigadores de robótica, Simulink®, y cuenta con un autopiloto de respaldo, PX4, para enfrentarse a los incidentes inesperados que pudieran surgir en vuelo

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics

Mission programming for flying ensembles: combining planning with self-organization

The application of autonomous mobile robots can improve many situations of our daily lives. Robots can enhance working conditions, provide innovative techniques for different research disciplines, and support rescue forces in an emergency. In particular, flying robots have already shown their potential in many use-cases when cooperating in ensembles. Exploiting this potential requires sophisticated measures for the goal-oriented, application-specific programming of flying ensembles and the coordinated execution of so defined programs. Because different goals require different robots providing different capabilities, several software approaches emerged recently that focus on specifically designed robots. These approaches often incorporate autonomous planning, scheduling, optimization, and reasoning attributable to classic artificial intelligence. This allows for the goal-oriented instruction of ensembles, but also leads to inefficiencies if ensembles grow large or face uncertainty in the environment. By leaving the detailed planning of executions to individuals and foregoing optimality and goal-orientation, the selforganization paradigm can compensate for these drawbacks by scalability and robustness. In this thesis, we combine the advantageous properties of autonomous planning with that of self-organization in an approach to Mission Programming for Flying Ensembles. Furthermore, we overcome the current way of thinking about how mobile robots should be designed. Rather than assuming fixed-design robots, we assume that robots are modifiable in terms of their hardware at run-time. While using such robots enables their application in many different use cases, it also requires new software approaches for dealing with this flexible design. The contributions of this thesis thus are threefold. First, we provide a layered reference architecture for physically reconfigurable robot ensembles. Second, we provide a solution for programming missions for ensembles consisting of such robots in a goal-oriented fashion that provides measures for instructing individual robots or entire ensembles as desired in the specific use case. Third, we provide multiple self-organization mechanisms to deal with the system’s flexible design while executing such missions. Combining different self-organization mechanisms ensures that ensembles satisfy the static requirements of missions. We provide additional self-organization mechanisms for coordinating the execution in ensembles ensuring they meet the dynamic requirements of a mission. Furthermore, we provide a solution for integrating goal-oriented swarm behavior into missions using a general pattern we have identified for trajectory-modification-based swarm behavior. Using that pattern, we can modify, quantify, and further process the emergent effect of varying swarm behavior in a mission by changing only the parameters of its implementation. We evaluate results theoretically and practically in different case studies by deploying our techniques to simulated and real hardware.Der Einsatz von autonomen mobilen Robotern kann viele Abläufe unseres täglichen Lebens erleichtern. Ihr Einsatz kann Arbeitsbedingungen verbessern, als innovative Technik für verschiedene Forschungsdisziplinen dienen oder Rettungskräfte im Einsatz unterstützen. Insbesondere Flugroboter haben ihr Potenzial bereits in vielerlei Anwendungsfällen gezeigt, gerade wenn mehrere in Ensembles eingesetzt werden. Das Potenzial fliegender Ensembles zielgerichtet und anwendungsspezifisch auszuschöpfen erfordert ausgefeilte Programmiermethoden und Koordinierungsverfahren. Zu diesem Zweck sind zuletzt viele unterschiedliche und auf speziell entwickelte Roboter zugeschnittene Softwareansätze entstanden. Diese verwenden oft klassische Planungs-, Scheduling-, Optimierungs- und Reasoningverfahren. Während dies vor allem den zielgerichteten Einsatz von Ensembles ermöglicht, ist es jedoch auch oft ineffizient, wenn die Ensembles größer oder deren Einsatzumgebungen unsicher werden. Die genannten Nachteile können durch das Paradigma der Selbstorganisation kompensiert werden: Falls Anwendungen nicht zwangsläufig auf Optimalität und strikte Zielorientierung ausgelegt sind, kann so Skalierbarkeit und Robustheit im System erreicht werden. In dieser Arbeit werden die vorteilhaften Eigenschaften klassischer Planungstechniken mit denen der Selbstorganisation in einem Ansatz zur Missionsprogrammierung für fliegende Ensembles kombiniert. In der dafür entwickelten Lösung wird von der aktuell etablierten Ansicht einer unveränderlichen Roboterkonstruktion abgewichen. Stattdessen wird die Hardwarezusammenstellung der Roboter als zur Laufzeit modifizierbar angesehen. Der Einsatz solcher Roboter erfordert neue Softwareansätze um mit genannter Flexibilität umgehen zu können. Die hier vorgestellten Beiträge zu diesem Thema lassen sich in drei Punkten zusammenfassen: Erstens wird eine Schichtenarchitektur als Referenz für physikalisch konfigurierbare Roboterensembles vorgestellt. Zweitens wird eine Lösung zur zielorientierten Missions-Programmierung für derartige Ensembles präsentiert, mit der sowohl einzelne Roboter als auch ganze Ensembles instruiert werden können. Drittens werden mehrere Selbstorganisationsmechanismen vorgestellt, die die autonome Ausführung so erstellter Missionen ermöglichen. Durch die Kombination verschiedener Selbstorganisationsmechanismen wird sichergestellt, dass Ensembles die missionsspezifischen Anforderungen erfüllen. Zusätzliche Selbstorganisationsmechanismen ermöglichen die koordinierte Ausführung der Missionen durch die Ensembles. Darüber hinaus bietet diese Lösung die Möglichkeit der Integration zielorientierten Schwarmverhaltens. Durch ein allgemeines algorithmisches Verfahren für auf Trajektorien-Modifikation basierendes Schwarmverhalten können allein durch die Änderung des Parametersatzes unterschiedliche emergente Effekte in einer Mission erzielt, quantifiziert und weiterverarbeitet werden. Zur theoretischen und praktischen Evaluierung der Ergebnisse dieser Arbeit wurden die vorgestellten Techniken in verschiedenen Fallstudien auf simulierter sowie realer Hardware zum Einsatz gebracht