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See detailWhen I Look into Your Eyes: A Survey on Computer Vision Contributions for Human Gaze Estimation and Tracking
Cazzato, Dario UL; Leo, Marco; Distante, Cosimo et al

in Sensors (2020), 20(13), 3739

The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific ... [more ▼]

The automatic detection of eye positions, their temporal consistency, and their mapping into a line of sight in the real world (to find where a person is looking at) is reported in the scientific literature as gaze tracking. This has become a very hot topic in the field of computer vision during the last decades, with a surprising and continuously growing number of application fields. A very long journey has been made from the first pioneering works, and this continuous search for more accurate solutions process has been further boosted in the last decade when deep neural networks have revolutionized the whole machine learning area, and gaze tracking as well. In this arena, it is being increasingly useful to find guidance through survey/review articles collecting most relevant works and putting clear pros and cons of existing techniques, also by introducing a precise taxonomy. This kind of manuscripts allows researchers and technicians to choose the better way to move towards their application or scientific goals. In the literature, there exist holistic and specifically technological survey documents (even if not updated), but, unfortunately, there is not an overview discussing how the great advancements in computer vision have impacted gaze tracking. Thus, this work represents an attempt to fill this gap, also introducing a wider point of view that brings to a new taxonomy (extending the consolidated ones) by considering gaze tracking as a more exhaustive task that aims at estimating gaze target from different perspectives: from the eye of the beholder (first-person view), from an external camera framing the beholder’s, from a third-person view looking at the scene where the beholder is placed in, and from an external view independent from the beholder. [less ▲]

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See detailA short Survey on the Cyber Security in Control Systems
Bezzaoucha, Souad UL; Voos, Holger UL

Scientific Conference (2020, July)

In the present survey paper, we give a short, yet exhaustive state-of-the-art about the cyber-security applied to control systems, especially the event-based strategy. Indeed, in the past few years, due ... [more ▼]

In the present survey paper, we give a short, yet exhaustive state-of-the-art about the cyber-security applied to control systems, especially the event-based strategy. Indeed, in the past few years, due to a highest degree of connectivity in modern systems, new related control-specific cyber-physical systems security challengesarise and novel approaches integrating the cyber aspect are developed.Our goal in this paper is then to provide an overview of attack-modeling and security analysis approaches in recent works thatexplore networked control systems subject to cyber-attacks attacks. To this end, we look at the control, estimation, and modeling problems. [less ▲]

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See detailOcular Biometrics Recognition by Analyzing Human Exploration during Video Observations
Cazzato, Dario; Carcagni, Pierluigi; Cimarelli, Claudio UL et al

in Applied Sciences (2020), 10(13), 4548

Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most ... [more ▼]

Soft biometrics provide information about the individual but without the distinctiveness and permanence able to discriminate between any two individuals. Since the gaze represents one of the most investigated human traits, works evaluating the feasibility of considering it as a possible additional soft biometric trait have been recently appeared in the literature. Unfortunately, there is a lack of systematic studies on clinically approved stimuli to provide evidence of the correlation between exploratory paths and individual identities in “natural” scenarios (without calibration, imposed constraints, wearable tools). To overcome these drawbacks, this paper analyzes gaze patterns by using a computer vision based pipeline in order to prove the correlation between visual exploration and user identity. This correlation is robustly computed in a free exploration scenario, not biased by wearable devices nor constrained to a prior personalized calibration. Provided stimuli have been designed by clinical experts and then they allow better analysis of human exploration behaviors. In addition, the paper introduces a novel public dataset that provides, for the first time, images framing the faces of the involved subjects instead of only their gaze tracks. [less ▲]

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See detailAn Integrated Teleoperation Assistance System for Collision Avoidance of High-speed UAVs in Complex Environments
Wang, Min UL; Voos, Holger UL

in 17th International Conference on Ubiquitous Robots (UR), Kyoto 22-26 June 2020 (2020, June)

UAV teleoperation is a demanding task, especially for amateur operators who wish to successfully accomplish their mission without collision. In this work we present an integrated 2D LIDAR based Sense-and ... [more ▼]

UAV teleoperation is a demanding task, especially for amateur operators who wish to successfully accomplish their mission without collision. In this work we present an integrated 2D LIDAR based Sense-and-Avoid system which actively assists unskilled human operator in obstacle avoidance, so that the operator can focus on higher-level decisions and global objectives in UAV applications such as search and rescue, farming etc. Specifically, with our perception-assistive vehicle control design, novel adaptive virtual cushion force field (AVCFF) based avoidance strategy, and integrated sensing solution, the proposed UAV teleoperation assistance system is capable of obstacle detection and tracking, as well as automatic avoidance in complex environment where both static and dynamic objects are present. The proposed system is constructed on the basis of Hector Quadrotor open source framework [1], and its effectiveness is demonstrated and validated on a realistic simulated UAV platform in Gazebo simulations where the UAV is operated at a high speed. [less ▲]

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See detailA Real-Time Approach for Chance-Constrained Motion Planning with Dynamic Obstacles
Castillo Lopez, Manuel UL; Ludivig, Philippe; Sajadi-Alamdari, Seyed Amin et al

in IEEE Robotics and Automation Letters (2020), 5(2), 3620-3625

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies ... [more ▼]

Uncertain dynamic obstacles, such as pedestrians or vehicles, pose a major challenge for optimal robot navigation with safety guarantees. Previous work on motion planning has followed two main strategies to provide a safe bound on an obstacle's space: a polyhedron, such as a cuboid, or a nonlinear differentiable surface, such as an ellipsoid. The former approach relies on disjunctive programming, which has a relatively high computational cost that grows exponentially with the number of obstacles. The latter approach needs to be linearized locally to find a tractable evaluation of the chance constraints, which dramatically reduces the remaining free space and leads to over-conservative trajectories or even unfeasibility. In this work, we present a hybrid approach that eludes the pitfalls of both strategies while maintaining the original safety guarantees. The key idea consists in obtaining a safe differentiable approximation for the disjunctive chance constraints bounding the obstacles. The resulting nonlinear optimization problem is free of chance constraint linearization and disjunctive programming, and therefore, it can be efficiently solved to meet fast real-time requirements with multiple obstacles. We validate our approach through mathematical proof, simulation and real experiments with an aerial robot using nonlinear model predictive control to avoid pedestrians. [less ▲]

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See detailA Preliminary Study on the Automatic Visual based Identification of UAV Pilots from Counter UAVs
Cazzato, Dario; Cimarelli, Claudio UL; Voos, Holger UL

in 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, Valletta 27-29 February 2020 (2020, February 27)

Two typical Unmanned Aerial Vehicles (UAV) countermeasures involve the detection and tracking of the UAV position, as well as of the human pilot; they are of critical importance before taking any ... [more ▼]

Two typical Unmanned Aerial Vehicles (UAV) countermeasures involve the detection and tracking of the UAV position, as well as of the human pilot; they are of critical importance before taking any countermeasure, and they already obtained strong attention from national security agencies in different countries. Recent advances in computer vision and artificial intelligence are already proposing many visual detection systems from an operating UAV, but they do not focus on the problem of the detection of the pilot of another approaching unauthorized UAV. In this work, a first attempt of proposing a full autonomous pipeline to process images from a flying UAV to detect the pilot of an unauthorized UAV entering a no-fly zone is introduced. A challenging video sequence has been created flying with a UAV in an urban scenario and it has been used for this preliminary evaluation. Experiments show very encouraging results in terms of recognition, and a complete dataset to evaluate artificial intelligence-based solution will be prepared. [less ▲]

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See detailSafer UAV Piloting: A Robust Sense-and-Avoid Solution for Remotely Piloted Quadrotor UAVs in Complex Environments
Wang, Min UL; Voos, Holger UL

in Safer UAV Piloting: A Robust Sense-and-Avoid Solution for Remotely Piloted Quadrotor UAVs in Complex Environments (2019, December)

Current commercial UAVs are to a large extent remotely piloted by amateur human pilots. Due to lack of teleoperation experience or skills, they often drive the UAVs into collision. Therefore, in order to ... [more ▼]

Current commercial UAVs are to a large extent remotely piloted by amateur human pilots. Due to lack of teleoperation experience or skills, they often drive the UAVs into collision. Therefore, in order to ensure safety of the UAV as well as its surroundings, it is necessary for the UAV to boast the capability of detecting emergency situation and acting on its own when facing imminent threat. However, the majority of UAVs currently available in the market are not equipped with such capability. To fill in the gap, in this paper we present a complete sense-and-avoid solution for assisting unskilled pilots in ensuring a safe flight. Particularly, we propose a novel nonlinear vehicle control system which takes into account of sensor characteristics, an emergency evaluation policy and a novel optimization-based avoidance control strategy. The effectiveness of the proposed approach is demonstrated and validated in simulation with multiple moving objects. [less ▲]

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See detailA case study on the impact of masking moving objects on the camera pose regression with CNNs
Cimarelli, Claudio UL; Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL et al

in 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) (2019, November 25)

Robot self-localization is essential for operating autonomously in open environments. When cameras are the main source of information for retrieving the pose, numerous challenges are posed by the presence ... [more ▼]

Robot self-localization is essential for operating autonomously in open environments. When cameras are the main source of information for retrieving the pose, numerous challenges are posed by the presence of dynamic objects, due to occlusion and continuous changes in the appearance. Recent research on global localization methods focused on using a single (or multiple) Convolutional Neural Network (CNN) to estimate the 6 Degrees of Freedom (6-DoF) pose directly from a monocular camera image. In contrast with the classical approaches using engineered feature detector, CNNs are usually more robust to environmental changes in light and to occlusions in outdoor scenarios. This paper contains an attempt to empirically demonstrate the ability of CNNs to ignore dynamic elements, such as pedestrians or cars, through learning. For this purpose, we pre-process a dataset for pose localization with an object segmentation network, masking potentially moving objects. Hence, we compare the pose regression CNN trained and/or tested on the set of masked images and the original one. Experimental results show that the performances of the two training approaches are similar, with a slight reduction of the error when hiding occluding objects from the views. [less ▲]

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See detailOn the Event-based Attack-tolerant Control: A Polytopic Representation
Bezzaoucha, Souad UL; Voos, Holger UL

in Bezzaoucha, Souad (Ed.) International Conference on Automation, Control and Robots (2019, October)

In the present contribution, we present a new event-based control representation. Based on the polytopic approach, more specifically the sector nonlinear transformation, an event-based attack-tolerant ... [more ▼]

In the present contribution, we present a new event-based control representation. Based on the polytopic approach, more specifically the sector nonlinear transformation, an event-based attack-tolerant control, and scheduling co-design strategy are proposed. From the event triggering definition (sample-and-hold strategy), polytopic writing of the event-triggered feedback control is first presented and then incorporated into the system dynamics for analysis. Our goal is to present a unique model that is able to deal with the co-design problem simultaneously and that can be handled by classical control synthesis tools. The novel representation, including data deception and attack tolerant control is formulated as a BMI optimization problem ensuring both stability and some level performance requirements (L2 attenuation of the cyber-attack). [less ▲]

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See detailSimultaneous State and False-Data Injection Attacks Reconstruction for NonLinear Systems: an LPV Approach
Bezzaoucha, Souad UL; Voos, Holger UL

in Bezzaoucha, Souad (Ed.) International Conference on Automation, Control and Robots (2019, October)

The present contribution addresses simultaneous state and actuator/sensor false-data injection attacks reconstruction for nonlinear systems. The considered actuator/sensor attacks are modeled as time ... [more ▼]

The present contribution addresses simultaneous state and actuator/sensor false-data injection attacks reconstruction for nonlinear systems. The considered actuator/sensor attacks are modeled as time-varying parameters with a multiplicative effect on the actuator input signal and the sensor output signal, respectively. Based on the sector non-linearity approach and the convex polytopic transformation, the nonlinear model is written in a Linear Parameter-Varying (LPV) form, then an observer allowing both state and attack reconstruction is designed by solving an LMI optimization problem. [less ▲]

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See detailVision-Based Aircraft Pose Estimation for UAVs Autonomous Inspection without Fiducial Markers
Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL; Sanchez Lopez, Jose Luis UL et al

in IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society (2019, October)

The reliability of aircraft inspection is of paramountimportance to safety of flights. Continuing airworthiness of air-craft structures is largely based upon the visual detection of smalldefects made by ... [more ▼]

The reliability of aircraft inspection is of paramountimportance to safety of flights. Continuing airworthiness of air-craft structures is largely based upon the visual detection of smalldefects made by trained inspection personnel with expensive,critical and time consuming tasks. At this aim, Unmanned AerialVehicles (UAVs) can be used for autonomous inspections, aslong as it is possible to localize the target while flying aroundit and correct the position. This work proposes a solution todetect the airplane pose with regards to the UAVs position whileflying autonomously around the airframe at close range forvisual inspection tasks. The system works by processing imagescoming from an RGB camera mounted on board, comparingincoming frames with a database of natural landmarks whoseposition on the airframe surface is known. The solution has beentested in real UAV flight scenarios, showing its effectiveness inlocalizing the pose with high precision. The advantages of theproposed methods are of industrial interest since we remove manyconstraint that are present in the state of the art solutions. [less ▲]

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See detailFaster Visual-Based Localization with Mobile-PoseNet
Cimarelli, Claudio UL; Cazzato, Dario UL; Olivares Mendez, Miguel Angel UL et al

in International Conference on Computer Analysis of Images and Patterns (2019, August 22)

Precise and robust localization is of fundamental importance for robots required to carry out autonomous tasks. Above all, in the case of Unmanned Aerial Vehicles (UAVs), efficiency and reliability are ... [more ▼]

Precise and robust localization is of fundamental importance for robots required to carry out autonomous tasks. Above all, in the case of Unmanned Aerial Vehicles (UAVs), efficiency and reliability are critical aspects in developing solutions for localization due to the limited computational capabilities, payload and power constraints. In this work, we leverage novel research in efficient deep neural architectures for the problem of 6 Degrees of Freedom (6-DoF) pose estimation from single RGB camera images. In particular, we introduce an efficient neural network to jointly regress the position and orientation of the camera with respect to the navigation environment. Experimental results show that the proposed network is capable of retaining similar results with respect to the most popular state of the art methods while being smaller and with lower latency, which are fundamental aspects for real-time robotics applications. [less ▲]

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See detailReal-Time Human Head Imitation for Humanoid Robots
Cazzato, Dario UL; Cimarelli, Claudio UL; Sanchez Lopez, Jose Luis UL et al

in Proceedings of the 2019 3rd International Conference on Artificial Intelligence and Virtual Reality (2019, July)

The ability of the robots to imitate human movements has been an active research study since the dawn of the robotics. Obtaining a realistic imitation is essential in terms of perceived quality in human ... [more ▼]

The ability of the robots to imitate human movements has been an active research study since the dawn of the robotics. Obtaining a realistic imitation is essential in terms of perceived quality in human-robot interaction, but it is still a challenge due to the lack of effective mapping between human movements and the degrees of freedom of robotics systems. If high-level programming interfaces, software and simulation tools simplified robot programming, there is still a strong gap between robot control and natural user interfaces. In this paper, a system to reproduce on a robot the head movements of a user in the field of view of a consumer camera is presented. The system recognizes the presence of a user and its head pose in real-time by using a deep neural network, in order to extract head position angles and to command the robot head movements consequently, obtaining a realistic imitation. At the same time, the system represents a natural user interface to control the Aldebaran NAO and Pepper humanoid robots with the head movements, with applications in human-robot interaction. [less ▲]

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See detailDeep learning based semantic situation awareness system for multirotor aerial robots using LIDAR
Sanchez Lopez, Jose Luis UL; Sampedro, Carlos; Cazzato, Dario UL et al

in 2019 International Conference on Unmanned Aircraft Systems (ICUAS) (2019, June)

In this work, we present a semantic situation awareness system for multirotor aerial robots, based on 2D LIDAR measurements, targeting the understanding of the environment and assuming to have a precise ... [more ▼]

In this work, we present a semantic situation awareness system for multirotor aerial robots, based on 2D LIDAR measurements, targeting the understanding of the environment and assuming to have a precise robot localization as an input of our algorithm. Our proposed situation awareness system calculates a semantic map of the objects of the environment as a list of circles represented by their radius, and the position and the velocity of their center in world coordinates. Our proposed algorithm includes three main parts. First, the LIDAR measurements are preprocessed and an object segmentation clusters the candidate objects present in the environment. Secondly, a Convolutional Neural Network (CNN) that has been designed and trained using an artificially generated dataset, computes the radius and the position of the center of individual circles in sensor coordinates. Finally, an indirect-EKF provides the estimate of the semantic map in world coordinates, including the velocity of the center of the circles in world coordinates.We have quantitative and qualitative evaluated the performance of our proposed situation awareness system by means of Software-In-The-Loop simulations using VRep with one and multiple static and moving cylindrical objects in the scene, obtaining results that support our proposed algorithm. In addition, we have demonstrated that our proposed algorithm is capable of handling real environments thanks to real laboratory experiments with non-cylindrical static (i.e. a barrel) and moving (i.e. a person) objects. [less ▲]

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See detailDeep Reinforcement Learning based Continuous Control for Multicopter Systems
Manukyan, Anush UL; Olivares Mendez, Miguel Angel UL; Geist, Matthieu et al

in International Conference on Control, Decision and Information CoDIT, Paris 23-26 April 2019 (2019, April 26)

In this paper we apply deep reinforcement learning techniques on a multicopter for learning a stable hovering task in a continuous action state environment. We present a framework based on OpenAI GYM ... [more ▼]

In this paper we apply deep reinforcement learning techniques on a multicopter for learning a stable hovering task in a continuous action state environment. We present a framework based on OpenAI GYM, Gazebo and RotorS MAV simulator, utilized for successfully training different agents to perform various tasks. The deep reinforcement learning method used for the training is model-free, on-policy, actor-critic based algorithm called Trust Region Policy Optimization (TRPO). Two neural networks have been used as a nonlinear function approximators. Our experiments showed that such learning approach achieves successful results, and facilitates the process of controller design. [less ▲]

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See detailAn Effective Hybrid Imperialist Competitive Algorithm and Tabu Search for an Extended Flexible Job Shop Scheduling Problem
Tessaro Lunardi, Willian UL; Voos, Holger UL; Cherri, Luiz Henrique

in 34th ACM/SIGAPP Symposium On Applied Computing, Limassol, Cyprus April 8-12, 2019 (2019, April 08)

An extended version of the flexible job shop problem is tackled in this work. The investigated extension of the classical flexible job shop problem allows the precedences between the operations to be ... [more ▼]

An extended version of the flexible job shop problem is tackled in this work. The investigated extension of the classical flexible job shop problem allows the precedences between the operations to be given by an arbitrary directed acyclic graph instead of a linear order. The problem consists of designating the operations to the machines and sequencing them in compliance with the supplied precedences. The goal in the present work is the minimization of the makespan. In order to produce reasonable outcomes in acceptable time, a hybrid imperialist competitive algorithm and tabu search is proposed to solve the problem. Numerical experiments assess the efficiency of the proposed method and compare it with well-known scheduling algorithms. [less ▲]

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See detailStability Analysis of Power Networks under Cyber-Physical Attacks: an LPV-Descriptor Approach
Bezzaoucha, Souad UL; Voos, Holger UL

in Bezzaoucha, Souad (Ed.) International Conference on Control, Decision and Information Technologies (2019, April)

This paper proposes a unified and advanced framework for the modeling, stability study and stabilization of a Power Networks subject to an omniscient adversary (i.e. cyber-attack). From the system model ... [more ▼]

This paper proposes a unified and advanced framework for the modeling, stability study and stabilization of a Power Networks subject to an omniscient adversary (i.e. cyber-attack). From the system model developed in [24], based on the well-known sector non-linearity approach and the convex polytopic transformation, the attacked system (descriptor model) is re-written in a more convenient form (Linear Parameter Varying-LPV) with unmeasurable premise variables. The so-called Lyapunov-based methods are applied in order to study the stability and security problems despite the presence of cyber-attacks. The conditions will be given in terms of Linear- Bilinear Matrix Inequality LMI- BMI constraints. [less ▲]

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See detailEvaluation of End-To-End Learning for Autonomous Driving: The Good, the Bad and the Ugly
Varisteas, Georgios UL; Frank, Raphaël UL; Sajadi Alamdari, Seyed Amin UL et al

in 2nd International Conference on Intelligent Autonomous Systems, Singapore, Feb. 28 to Mar. 2, 2019 (2019, March 01)

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See detailA Real-Time 3D Path Planning Solution for Collision-Free Navigation of Multirotor Aerial Robots in Dynamic Environments
Sanchez Lopez, Jose Luis UL; Wang, Min UL; Olivares Mendez, Miguel Angel UL et al

in Journal of Intelligent and Robotic Systems (2019), 93(1-2), 33-53

Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for ... [more ▼]

Deliberative capabilities are essential for intelligent aerial robotic applications in modern life such as package delivery and surveillance. This paper presents a real-time 3D path planning solution for multirotor aerial robots to obtain a feasible, optimal and collision-free path in complex dynamic environments. High-level geometric primitives are employed to compactly represent the situation, which includes self-situation of the robot and situation of the obstacles in the environment. A probabilistic graph is utilized to sample the admissible space without taking into account the existing obstacles. Whenever a planning query is received, the generated probabilistic graph is then explored by an A$^{\star}$ discrete search algorithm with an artificial field map as cost function in order to obtain a raw optimal collision-free path, which is subsequently shortened. Realistic simulations in V-REP simulator have been created to validate the proposed path planning solution, integrating it into a fully autonomous multirotor aerial robotic system. [less ▲]

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See detailNew Trends in Observer-based Control: An Introduction to Design Approaches and Engineering Applications, Chapter 13: Observer-based Event-triggered Attack-Tolerant Control Design for Cyber-physical Systems
Bezzaoucha, Souad UL; Voos, Holger UL

in New Trends in Observer-based Control: An Introduction to Design Approaches and Engineering Applications, Chapter 13: Observer-based Event-triggered Attack-Tolerant Control Design for Cyber-physical Systems (2019)

In the following chapter, we first introduce an appropriate model associating paradigms from control theory and computer science (system subject to both physical attacks and sensors/actuators attacks via ... [more ▼]

In the following chapter, we first introduce an appropriate model associating paradigms from control theory and computer science (system subject to both physical attacks and sensors/actuators attacks via the connected network, i.e., false-data injection attacks on actuators/sensors). Then, inspired by a combination between the classical fault-tolerant control (FTC) approach and the event-triggered control, an observer-based attack-tolerant control solution is proposed. The aim of our work is, first, to establish theoretical foundations for the development of model-based monitoring and attack-tolerant control for reliable deployment of a large number of advanced Cyber-Physical Systems. [less ▲]

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