References of "Voos, Holger 50003283"
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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 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 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 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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See detailA parallel multi-population biased random-key genetic algorithm for electric distribution network reconfiguration
de Faria Junior, Haroldo UL; Tessaro Lunardi, Willian UL; Voos, Holger UL

in The Genetic and Evolutionary Computation Conference - GECCO'19 (2019)

This work presents a multi-population biased random-key genetic algorithm (BRKGA) for the electric distribution network reconfiguration problem (DNR). DNR belongs to the class of network design problems ... [more ▼]

This work presents a multi-population biased random-key genetic algorithm (BRKGA) for the electric distribution network reconfiguration problem (DNR). DNR belongs to the class of network design problems which include transportation problems, computer network restoration and telecommunication network design and can be used for loss minimization and load balancing, being an important tool for distribution network operators. A BRKGA is a class of genetic algorithms in which solutions are encoded as vectors of random keys, i.e. randomly generated real numbers from a uniform distribution in the interval [0, 1). A vector of random keys is translated into a solution of the optimization problem by a decoder. The decoder used generates only feasible solutions by using an efficient codification based upon the fundamentals of graph theory, restricting the search space. The parallelization is based on the single program multiple data paradigm and is executed on the cores of a multi-core processor. Time to target plots, which characterize the running times of stochastic algorithms for combinatorial optimization, are used to compare the performance of the serial and parallel algorithms. The proposed method has been tested on two standard distribution systems and the results show the effectiveness and performance of the parallel algorithm. [less ▲]

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See detailUnderstanding and Modelling Human Attention for Soft Biometrics Purposes
Cazzato, Dario UL; Leo, Marco; Carcagnì, Pierluigi et al

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

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See detailA non-invasive tool for attention-deficit disorder analysis based on gaze tracks
Cazzato, Dario UL; Castro, Silvia M.; Agamennoni, Osvaldo et al

in Proceedings of the 2nd International Conference on Applications of Intelligent Systems (2019)

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See detailVideo Indexing Using Face Appearance and Shot Transition Detection
Cazzato, Dario UL; Leo, Marco; Carcagni, Pierluigi et al

in Proceedings of the IEEE International Conference on Computer Vision Workshops (2019)

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See detailNonlinear Model Predictive Control for Ecological Driver Assistance Systems in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in Robotics and Autonomous Systems (2018)

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See detailEcological Advanced Driver Assistance System for Optimal Energy Management in Electric Vehicles
Sajadi Alamdari, Seyed Amin UL; Voos, Holger UL; Darouach, Mohamed

in IEEE Intelligent Transportation Systems Magazine (2018)

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and ... [more ▼]

Battery Electric Vehicles have a high potential in modern transportation, however, they are facing limited cruising range. The driving style, the road geometries including slopes, curves, the static and dynamic traffic conditions such as speed limits and preceding vehicles have their share of energy consumption in the host electric vehicle. Optimal energy management based on a semi-autonomous ecological advanced driver assistance system can improve the longitudinal velocity regulation in a safe and energy-efficient driving strategy. The main contribution of this paper is the design of a real-time risk-sensitive nonlinear model predictive controller to plan the online cost-effective cruising velocity in a stochastic traffic environment. The basic idea is to measure the relevant states of the electric vehicle at runtime, and account for the road slopes, the upcoming curves, and the speed limit zones, as well as uncertainty in the preceding vehicle behavior to determine the energy-efficient velocity profile. Closed-loop Entropic Value-at-Risk as a coherent risk measure is introduced to quantify the risk involved in the system constraints violation. The obtained simulation and field experimental results demonstrate the effectiveness of the proposed method for a semi-autonomous electric vehicle in terms of safe and energy-efficient states regulation and constraints satisfaction. [less ▲]

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See detailAn Imperialist Competitive Algorithm for a Real-World Flexible Job Shop Scheduling Problem
Tessaro Lunardi, Willian UL; Voos, Holger UL; Cherri, Luiz Henrique

in 23rd IEEE International Conference on Emerging Technologies and Factory Automation, Torino, Italy, September 4-7, 2018 (2018, September)

Traditional planning and scheduling techniques still hold important roles in modern smart scheduling systems. Realistic features present in modern manufacturing systems need to be incorporated into these ... [more ▼]

Traditional planning and scheduling techniques still hold important roles in modern smart scheduling systems. Realistic features present in modern manufacturing systems need to be incorporated into these techniques. The real-world problem addressed here is an extension of flexible job shop scheduling problem and is issued from the modern printing and boarding industry. The precedence between operations of each job is given by an arbitrary directed acyclic graph rather than a linear order. In this paper, we extend the traditional FJSP solutions representation to address the parallel operations. We propose an imperialist competitive algorithm for the problem. Several instances are used for the experiments and the results show that, for the considered instances, the proposed algorithm is faster and found better or equal solutions compared to the state-of-the-art algorithms. [less ▲]

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