Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

Towards edge robotics: the progress from cloud-based robotic systems to intelligent and context-aware robotic services

Current robotic systems handle a different range of applications such as video surveillance, delivery of goods, cleaning, material handling, assembly, painting, or pick and place services. These systems have been embraced not only by the general population but also by the vertical industries to help them in performing daily activities. Traditionally, the robotic systems have been deployed in standalone robots that were exclusively dedicated to performing a specific task such as cleaning the floor in indoor environments. In recent years, cloud providers started to offer their infrastructures to robotic systems for offloading some of the robot’s functions. This ultimate form of the distributed robotic system was first introduced 10 years ago as cloud robotics and nowadays a lot of robotic solutions are appearing in this form. As a result, standalone robots became software-enhanced objects with increased reconfigurability as well as decreased complexity and cost. Moreover, by offloading the heavy processing from the robot to the cloud, it is easier to share services and information from various robots or agents to achieve better cooperation and coordination. Cloud robotics is suitable for human-scale responsive and delay-tolerant robotic functionalities (e.g., monitoring, predictive maintenance). However, there is a whole set of real-time robotic applications (e.g., remote control, motion planning, autonomous navigation) that can not be executed with cloud robotics solutions, mainly because cloud facilities traditionally reside far away from the robots. While the cloud providers can ensure certain performance in their infrastructure, very little can be ensured in the network between the robots and the cloud, especially in the last hop where wireless radio access networks are involved. Over the last years advances in edge computing, fog computing, 5G NR, network slicing, Network Function Virtualization (NFV), and network orchestration are stimulating the interest of the industrial sector to satisfy the stringent and real-time requirements of their applications. Robotic systems are a key piece in the industrial digital transformation and their benefits are very well studied in the literature. However, designing and implementing a robotic system that integrates all the emerging technologies and meets the connectivity requirements (e.g., latency, reliability) is an ambitious task. This thesis studies the integration of modern Information andCommunication Technologies (ICTs) in robotic systems and proposes some robotic enhancements that tackle the real-time constraints of robotic services. To evaluate the performance of the proposed enhancements, this thesis departs from the design and prototype implementation of an edge native robotic system that embodies the concepts of edge computing, fog computing, orchestration, and virtualization. The proposed edge robotics system serves to represent two exemplary robotic applications. In particular, autonomous navigation of mobile robots and remote-control of robot manipulator where the end-to-end robotic system is distributed between the robots and the edge server. The open-source prototype implementation of the designed edge native robotic system resulted in the creation of two real-world testbeds that are used in this thesis as a baseline scenario for the evaluation of new innovative solutions in robotic systems. After detailing the design and prototype implementation of the end-to-end edge native robotic system, this thesis proposes several enhancements that can be offered to robotic systems by adapting the concept of edge computing via the Multi-Access Edge Computing (MEC) framework. First, it proposes exemplary network context-aware enhancements in which the real-time information about robot connectivity and location can be used to dynamically adapt the end-to-end system behavior to the actual status of the communication (e.g., radio channel). Three different exemplary context-aware enhancements are proposed that aim to optimize the end-to-end edge native robotic system. Later, the thesis studies the capability of the edge native robotic system to offer potential savings by means of computation offloading for robot manipulators in different deployment configurations. Further, the impact of different wireless channels (e.g., 5G, 4G andWi-Fi) to support the data exchange between a robot manipulator and its remote controller are assessed. In the following part of the thesis, the focus is set on how orchestration solutions can support mobile robot systems to make high quality decisions. The application of OKpi as an orchestration algorithm and DLT-based federation are studied to meet the KPIs that autonomously controlledmobile robots have in order to provide uninterrupted connectivity over the radio access network. The elaborated solutions present high compatibility with the designed edge robotics system where the robot driving range is extended without any interruption of the end-to-end edge robotics service. While the DLT-based federation extends the robot driving range by deploying access point extension on top of external domain infrastructure, OKpi selects the most suitable access point and computing resource in the cloud-to-thing continuum in order to fulfill the latency requirements of autonomously controlled mobile robots. To conclude the thesis the focus is set on how robotic systems can improve their performance by leveraging Artificial Intelligence (AI) and Machine Learning (ML) algorithms to generate smart decisions. To do so, the edge native robotic system is presented as a true embodiment of a Cyber-Physical System (CPS) in Industry 4.0, showing the mission of AI in such concept. It presents the key enabling technologies of the edge robotic system such as edge, fog, and 5G, where the physical processes are integrated with computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure level. In the last part of the thesis, the movement prediction is selected to study the feasibility of applying a forecast-based recovery mechanism for real-time remote control of robotic manipulators (FoReCo) that uses ML to infer lost commands caused by interference in the wireless channel. The obtained results are showcasing the its potential in simulation and real-world experimentation.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Karl Holger.- Secretario: Joerg Widmer.- Vocal: Claudio Cicconett

Dissecting the impact of information and communication technologies on digital twins as a service

Recent advances on Edge computing, Network Function Virtualization (NFV) and 5G are stimulating the interest of the industrial sector to satisfy the stringent and real-time requirements of their applications. Digital Twin is a key piece in the industrial digital transformation and its benefits are very well studied in the literature. However, designing and implementing a Digital Twin system that integrates all the emerging technologies and meets the connectivity requirements (e.g., latency, reliability) is an ambitious task. Therefore, prototyping the system is required to gradually validate and optimize Digital Twin solutions. In this work, an Edge Robotics Digital Twin system is implemented as a prototype that embodies the concept of Digital Twin as a Service (DTaaS). Such system enables real-time applications such as visualization and remote control, requiring low-latency and high reliability. The capability of the system to offer potential savings by means of computation offloading are analyzed in different deployment configurations. Moreover, the impact of different wireless channels (e.g., 5G, 4G and WiFi) to support the data exchange between a physical device and its virtual components are assessed within operational Digital Twins. Results show that potentially 16% of CPU and 34% of MEM savings can be achieved by virtualizing and offloading software components in the Edge. In addition, they show that 5G connectivity enables remote control of 20 ms, appearing as the most promising radio access technology to support the main requirements of Digital Twin systems.This work was supported in part by the H2020 European Union/Taiwan (EU/TW) Joint Action 5G-eDge Intelligence for Vertical Experimentation (DIVE) under Grant 859881, in part by the H2020 5Growth Project under Grant 856709, in part by the Madrid Government (Comunidad de Madrid-Spain) through the Multiannual Agreement with Universidad Carlos III de Madrid (UC3M) in the line of Excellence of University Professors under Grant EPUC3M21, and in part by the context of the V PRICIT (Regional Program of Research and Technological Innovation)

Internet of Robotic Things Intelligent Connectivity and Platforms

The Internet of Things (IoT) and Industrial IoT (IIoT) have developed rapidly in the past few years, as both the Internet and “things” have evolved significantly. “Things” now range from simple Radio Frequency Identification (RFID) devices to smart wireless sensors, intelligent wireless sensors and actuators, robotic things, and autonomous vehicles operating in consumer, business, and industrial environments. The emergence of “intelligent things” (static or mobile) in collaborative autonomous fleets requires new architectures, connectivity paradigms, trustworthiness frameworks, and platforms for the integration of applications across different business and industrial domains. These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT). In IoRT, collaborative robotic things can communicate with other things, learn autonomously, interact safely with the environment, humans and other things, and gain qualities like self-maintenance, self-awareness, self-healing, and fail-operational behavior. IoRT applications can make use of the individual, collaborative, and collective intelligence of robotic things, as well as information from the infrastructure and operating context to plan, implement and accomplish tasks under different environmental conditions and uncertainties. The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms important components of new-generation IoRT applications. This paper reviews the taxonomy of the IoRT, emphasizing the IoRT intelligent connectivity, architectures, interoperability, and trustworthiness framework, and surveys the technologies that enable the application of the IoRT across different domains to perform missions more efficiently, productively, and completely. The aim is to provide a novel perspective on the IoRT that involves communication among robotic things and humans and highlights the convergence of several technologies and interactions between different taxonomies used in the literature.publishedVersio

Resource Requirements of an Edge-based Digital Twin Service: An Experimental Study

Digital Twin (DT) is a pivotal application under the industrial digital transformation envisaged by the fourth industrial revolution (Industry 4.0). DT defines intelligent and real-time faithful reflections of physical entities such as industrial robots, thus allowing their remote control. Relying on the latest advances in Information and Communication Technologies (ICT), namely Network Function Virtualization (NFV) and Edge-computing, DT can be deployed as an on-demand service in the factories close proximity and offered leveraging radio access technologies. However, with the purpose of achieving the well-known scalability, flexibility, availability and performance guarantees benefits foreseen by the latest ICT, it is steadily required to experimentally profile and assess DT as a Service (DTaaS) solutions. Moreover, the dependencies between the resources claimed by the service and the relative demand and work loads require to be investigated. In this work, an Edge-based Digital Twin solution for remote control of robotic arms is deployed in an experimental testbed where, in compliance with the NFV paradigm, the service has been segmented in virtual network functions. Our research has primarily the objective to evaluate the entanglement among overall service performance and VNFs resource requirements, and the number of robots consuming the service varies. Experimental profiles show the most critical DT features to be the inverse kinematics and trajectory computations. Moreover, the same analysis has been carried out as a function of the industrial processes, namely based on the commands imposed on the robots, and particularly of their abstraction-level, resulting in a novel trade-off between computing and time resources requirements and trajectory guarantees. The derived results provide crucial insights for the design of network service scaling and resource orchestration frameworks dealing with DTaaS applications. Finally, we empirically prove LTE shortage to accommodate the minimum DT latency requirements

Performance and efficiency optimization of multi-layer IoT edge architecture

Abstract. Internet of Things (IoT) has become a backbone technology that connects together various devices with diverse capabilities. It is a technology, which enables ubiquitously available digital services for end-users. IoT applications for mission-critical scenarios need strict performance indicators such as of latency, scalability, security and privacy. To fulfil these requirements, IoT also requires support from relevant enabling technologies, such as cloud, edge, virtualization and fifth generation mobile communication (5G) technologies. For Latency-critical applications and services, long routes between the traditional cloud server and end-devices (sensors /actuators) is not a feasible approach for computing at these data centres, although these traditional clouds provide very high computational and storage for current IoT system. MEC model can be used to overcome this challenge, which brings the CC computational capacity within or next on the access network base stations. However, the capacity to perform the most critical processes at the local network layer is often necessary to cope with the access network issues. Therefore, this thesis compares the two existing IoT models such as traditional cloud-IoT model, a MEC-based edge-cloud-IoT model, with proposed local edge-cloud-IoT model with respect to their performance and efficiency, using iFogSim simulator. The results consolidate our research team’s previous findings that utilizing the three-tier edge-IoT architecture, capable of optimally utilizing the computational capacity of each of the three tiers, is an effective measure to reduce energy consumption, improve end-to-end latency and minimize operational costs in latency-critical It applications

Cloud Robotics for Industry 4.0 - A Literature Review

Robots in the industry have been used for decades, much before the so-called Fourth Industrial Revolution. They have been incorporated into industrial processes in various ways, for example, with mechanic arms, in assembly processes, welding, and painting, among others. Industrial robots are located in restricted access sites and their space is delimited by means of physical barriers and security measures. In recent years, Industry 4.0 proposes the use robots, able to collaborate with persons, known as collaborative robots or “cobots”. Cobots are characterized by cooperating with human work, sharing the same workspace, and able to respond to simple human-machine interactions. In addition, given the benefits of applying cloud computing in Industry 4.0, research has been conducted in applying such technologies to robots. The approach is known as “cloud robotics” and appears as an emerging topic. The objective of this work is to carry out a systematic literature review of cloud robotics for Industry 4.0, in an attempt to present the state of the art in this field and identify opportunities for future research. From the analysis of the results, we observe an emerging interest in this area, and we identify main technologies applied, research themes, and application areas, as well as a special interest on security and safety aspects.Part of the Communications in Computer and Information Science book series (CCIS, vol. 1291)Facultad de Informátic