1,267 research outputs found
A virtual actuator approach for the secure control of networked LPV systems under pulse-width modulated DoS attacks
In this paper, we formulate and analyze the problem of secure control in the context of networked linear parameter varying (LPV) systems. We consider an energy-constrained, pulse-width modulated (PWM) jammer, which corrupts the control communication channel by performing a denial-of-service (DoS) attack. In particular, the malicious attacker is able to erase the data sent to one or more actuators. In order to achieve secure control, we propose a virtual actuator technique under the assumption that the behavior of the attacker has been identified. The main advantage brought by this technique is that the existing components in the control system can be maintained without need of retuning them, since the virtual actuator will perform a reconfiguration of the plant, hiding the attack from the controller point of view. Using Lyapunov-based results that take into account the possible behavior of the attacker, design conditions for calculating the virtual actuators gains are obtained. A numerical example is used to illustrate the proposed secure control strategy.Peer ReviewedPostprint (author's final draft
How Physicality Enables Trust: A New Era of Trust-Centered Cyberphysical Systems
Multi-agent cyberphysical systems enable new capabilities in efficiency,
resilience, and security. The unique characteristics of these systems prompt a
reevaluation of their security concepts, including their vulnerabilities, and
mechanisms to mitigate these vulnerabilities. This survey paper examines how
advancement in wireless networking, coupled with the sensing and computing in
cyberphysical systems, can foster novel security capabilities. This study
delves into three main themes related to securing multi-agent cyberphysical
systems. First, we discuss the threats that are particularly relevant to
multi-agent cyberphysical systems given the potential lack of trust between
agents. Second, we present prospects for sensing, contextual awareness, and
authentication, enabling the inference and measurement of ``inter-agent trust"
for these systems. Third, we elaborate on the application of quantifiable trust
notions to enable ``resilient coordination," where ``resilient" signifies
sustained functionality amid attacks on multiagent cyberphysical systems. We
refer to the capability of cyberphysical systems to self-organize, and
coordinate to achieve a task as autonomy. This survey unveils the cyberphysical
character of future interconnected systems as a pivotal catalyst for realizing
robust, trust-centered autonomy in tomorrow's world
Smart Wireless Sensor Networks
The recent development of communication and sensor technology results in the growth of a new attractive and challenging area - wireless sensor networks (WSNs). A wireless sensor network which consists of a large number of sensor nodes is deployed in environmental fields to serve various applications. Facilitated with the ability of wireless communication and intelligent computation, these nodes become smart sensors which do not only perceive ambient physical parameters but also be able to process information, cooperate with each other and self-organize into the network. These new features assist the sensor nodes as well as the network to operate more efficiently in terms of both data acquisition and energy consumption. Special purposes of the applications require design and operation of WSNs different from conventional networks such as the internet. The network design must take into account of the objectives of specific applications. The nature of deployed environment must be considered. The limited of sensor nodesďż˝ resources such as memory, computational ability, communication bandwidth and energy source are the challenges in network design. A smart wireless sensor network must be able to deal with these constraints as well as to guarantee the connectivity, coverage, reliability and security of network's operation for a maximized lifetime. This book discusses various aspects of designing such smart wireless sensor networks. Main topics includes: design methodologies, network protocols and algorithms, quality of service management, coverage optimization, time synchronization and security techniques for sensor networks
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 IngenierĂa Telemática por la Universidad Carlos III de MadridPresidente: Karl Holger.- Secretario: Joerg Widmer.- Vocal: Claudio Cicconett
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
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