References of "Sanchez Lopez, Jose Luis 50027149"
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See detailSemantic situation awareness of ellipse shapes via deep learning for multirotor aerial robots with a 2D LIDAR
Sanchez Lopez, Jose Luis UL; Castillo Lopez, Manuel UL; Voos, Holger UL

in 2020 International Conference on Unmanned Aircraft Systems (ICUAS) (2020, September)

In this work, we present a semantic situation awareness system for multirotor aerial robots equipped with a 2D LIDAR sensor, focusing on the understanding of the environment, provided to have a drift-free ... [more ▼]

In this work, we present a semantic situation awareness system for multirotor aerial robots equipped with a 2D LIDAR sensor, focusing on the understanding of the environment, provided to have a drift-free precise localization of the robot (e.g. given by GNSS/INS or motion capture system). Our algorithm generates in real-time a semantic map of the objects of the environment as a list of ellipses represented by their radii, and their pose and velocity, both in world coordinates. Two different Convolutional Neural Network (CNN) architectures are proposed and trained using an artificially generated dataset and a custom loss function, to detect ellipses in a segmented (i.e. with one single object) LIDAR measurement. In cascade, a specifically designed indirect-EKF estimates the ellipses based semantic map in world coordinates, as well as their velocity. We have quantitative and qualitatively evaluated the performance of our proposed situation awareness system. Two sets of Software-In-The-Loop simulations using CoppeliaSim with one and multiple static and moving cylindrical objects are used to evaluate the accuracy and performance of our algorithm. In addition, we have demonstrated the robustness of our proposed algorithm when handling real environments thanks to real laboratory experiments with non-cylindrical static (i.e. a barrel) objects and moving persons. [less ▲]

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See detailA Survey of Computer Vision Methods for 2D Object Detection from Unmanned Aerial Vehicles
Cazzato, Dario UL; Cimarelli, Claudio UL; Sanchez Lopez, Jose Luis UL et al

in Journal of Imaging (2020), 6(8), 78

The spread of Unmanned Aerial Vehicles (UAVs) in the last decade revolutionized many applications fields. Most investigated research topics focus on increasing autonomy during operational campaigns ... [more ▼]

The spread of Unmanned Aerial Vehicles (UAVs) in the last decade revolutionized many applications fields. Most investigated research topics focus on increasing autonomy during operational campaigns, environmental monitoring, surveillance, maps, and labeling. To achieve such complex goals, a high-level module is exploited to build semantic knowledge leveraging the outputs of the low-level module that takes data acquired from multiple sensors and extracts information concerning what is sensed. All in all, the detection of the objects is undoubtedly the most important low-level task, and the most employed sensors to accomplish it are by far RGB cameras due to costs, dimensions, and the wide literature on RGB-based object detection. This survey presents recent advancements in 2D object detection for the case of UAVs, focusing on the differences, strategies, and trade-offs between the generic problem of object detection, and the adaptation of such solutions for operations of the UAV. Moreover, a new taxonomy that considers different heights intervals and driven by the methodological approaches introduced by the works in the state of the art instead of hardware, physical and/or technological constraints is proposed. [less ▲]

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See detailTrajectory Tracking for Aerial Robots: an Optimization-Based Planning and Control Approach
Sanchez Lopez, Jose Luis UL; Castillo Lopez, Manuel UL; Olivares Mendez, Miguel Angel UL et al

in Journal of Intelligent and Robotic Systems (2020), 100

In this work, we present an optimization-based trajectory tracking solution for multirotor aerial robots given a geometrically feasible path. A trajectory planner generates a minimum-time kinematically ... [more ▼]

In this work, we present an optimization-based trajectory tracking solution for multirotor aerial robots given a geometrically feasible path. A trajectory planner generates a minimum-time kinematically and dynamically feasible trajectory that includes not only standard restrictions such as continuity and limits on the trajectory, constraints in the waypoints, and maximum distance between the planned trajectory and the given path, but also restrictions in the actuators of the aerial robot based on its dynamic model, guaranteeing that the planned trajectory is achievable. Our novel compact multi-phase trajectory definition, as a set of two different kinds of polynomials, provides a higher semantic encoding of the trajectory, which allows calculating an optimal solution but following a predefined simple profile. A Model Predictive Controller ensures that the planned trajectory is tracked by the aerial robot with the smallest deviation. Its novel formulation takes as inputs all the magnitudes of the planned trajectory (i.e. position and heading, velocity, and acceleration) to generate the control commands, demonstrating through in-lab real flights an improvement of the tracking performance when compared with a controller that only uses the planned position and heading. To support our optimization-based solution, we discuss the most commonly used representations of orientations, as well as both the difference as well as the scalar error between two rotations, in both tridimensional and bidimensional spaces $SO(3)$ and $SO(2)$. We demonstrate that quaternions and error-quaternions have some advantages when compared to other formulations. [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 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 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 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 detailFast and Robust Flight Altitude Estimation of Multirotor UAVs in Dynamic Unstructured Environments Using 3D Point Cloud Sensors
Bavle, Hriday UL; Sanchez Lopez, Jose Luis UL; de la Puente, Paloma et al

in Aerospace (2018), 5(3),

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor ... [more ▼]

This paper presents a fast and robust approach for estimating the flight altitude of multirotor Unmanned Aerial Vehicles (UAVs) using 3D point cloud sensors in cluttered, unstructured, and dynamic indoor environments. The objective is to present a flight altitude estimation algorithm, replacing the conventional sensors such as laser altimeters, barometers, or accelerometers, which have several limitations when used individually. Our proposed algorithm includes two stages: in the first stage, a fast clustering of the measured 3D point cloud data is performed, along with the segmentation of the clustered data into horizontal planes. In the second stage, these segmented horizontal planes are mapped based on the vertical distance with respect to the point cloud sensor frame of reference, in order to provide a robust flight altitude estimation even in presence of several static as well as dynamic ground obstacles. We validate our approach using the IROS 2011 Kinect dataset available in the literature, estimating the altitude of the RGB-D camera using the provided 3D point clouds. We further validate our approach using a point cloud sensor on board a UAV, by means of several autonomous real flights, closing its altitude control loop using the flight altitude estimated by our proposed method, in presence of several different static as well as dynamic ground obstacles. In addition, the implementation of our approach has been integrated in our open-source software framework for aerial robotics called Aerostack. [less ▲]

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See detailModel Predictive Control for Aerial Collision Avoidance in Dynamic Environments
Castillo Lopez, Manuel UL; Sajadi Alamdari, Seyed Amin UL; Sanchez Lopez, Jose Luis UL et al

in 26th Mediterranean Conference on Control and Automation (MED), Zadar, Croatia, 19-22 June 2018 (2018, June)

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic ... [more ▼]

Autonomous navigation in unknown environments populated by humans and other robots is one of the main challenges when working with mobile robots. In this paper, we present a new approach to dynamic collision avoidance for multi-rotor unmanned aerial vehicles (UAVs). A new nonlinear model predictive control (NMPC) approach is proposed to safely navigate in a workspace populated by static and/or moving obstacles. The uniqueness of our approach lies in its ability to anticipate the dynamics of multiple obstacles, avoiding them in real-time. Exploiting active set algorithms, only the obstacles that affect to the UAV during the prediction horizon are considered at each sample time. We also improve the fluency of avoidance maneuvers by reformulating the obstacles as orientable ellipsoids, being less prone to local minima and allowing the definition of a preferred avoidance direction. Finally, we present two real-time implementations based on simulation. The former demonstrates that our approach outperforms its analog static formulation in terms of safety and efficiency. The latter shows its capability to avoid multiple dynamic obstacles. [less ▲]

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See detailTowards trajectory planning from a given path for multirotor aerial robots trajectory tracking
Sanchez Lopez, Jose Luis UL; Olivares Mendez, Miguel Angel UL; Castillo Lopez, Manuel UL et al

in 2018 International Conference on Unmanned Aircraft Systems (ICUAS), Dallas 12-15 June 2018 (2018, June)

Planning feasible trajectories given desired collision-free paths is an essential capability of multirotor aerial robots that enables the trajectory tracking task, in contrast to path following. This ... [more ▼]

Planning feasible trajectories given desired collision-free paths is an essential capability of multirotor aerial robots that enables the trajectory tracking task, in contrast to path following. This paper presents a trajectory planner for multirotor aerial robots carefully designed considering the requirements of real applications such as aerial inspection or package delivery, unlike other research works that focus on aggressive maneuvering. Our planned trajectory is formed by a set of polynomials of two kinds, acceleration/deceleration and constant velocity. The trajectory planning is carried out by means of an optimization that minimizes the trajectory tracking time, applying some typical constraints as m-continuity or limits on velocity, acceleration and jerk, but also the maximum distance between the trajectory and the given path. Our trajectory planner has been tested in real flights with a big and heavy aerial platform such the one that would be used in a real operation. Our experiments demonstrate that the proposed trajectory planner is suitable for real applications and it is positively influencing the controller for the trajectory tracking task. [less ▲]

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See detailA Multi-Layered Component-Based Approach for the Development of Aerial Robotic Systems: The Aerostack Framework
Sanchez Lopez, Jose Luis UL; Molina, Martin; Bavle, Hriday et al

in Journal of Intelligent and Robotic Systems (2017), 88(2), 638-709

To achieve fully autonomous operation for Unmanned Aerial Systems (UAS) it is necessary to integrate multiple and heterogeneous technical solutions (e.g., control-based methods, computer vision methods ... [more ▼]

To achieve fully autonomous operation for Unmanned Aerial Systems (UAS) it is necessary to integrate multiple and heterogeneous technical solutions (e.g., control-based methods, computer vision methods, automated planning, coordination algorithms, etc.). The combination of such methods in an operational system is a technical challenge that requires efficient architectural solutions. In a robotic engineering context, where productivity is important, it is also important to minimize the effort for the development of new systems. As a response to these needs, this paper presents Aerostack, an open-source software framework for the development of aerial robotic systems. This framework facilitates the creation of UAS by providing a set of reusable components specialized in functional tasks of aerial robotics (trajectory planning, self localization, etc.) together with an integration method in a multi-layered cognitive architecture based on five layers: reactive, executive, deliberative, reflective and social. Compared to other software frameworks for UAS, Aerostack can provide higher degrees of autonomy and it is more versatile to be applied to different types of hardware (aerial platforms and sensors) and different types of missions (e.g. multi robot swarm systems). Aerostack has been validated during four years (since February 2013) by its successful use on many research projects, international competitions and public exhibitions. As a representative example of system development, this paper also presents how Aerostack was used to develop a system for a (fictional) fully autonomous indoors search and rescue mission. [less ▲]

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See detailTML: a language to specify aerial robotic missions for the framework Aerostack
Molina, Martin; Suarez-Fernandez, Ramon; Sampedro, Carlos et al

in International Journal of Intelligent Computing and Cybernetics (2017), 10(4), 491-512

Purpose - The main purpose of this paper is to describe the specification language TML for adaptive mission plans that we designed and implemented for the open source framework Aerostack for aerial ... [more ▼]

Purpose - The main purpose of this paper is to describe the specification language TML for adaptive mission plans that we designed and implemented for the open source framework Aerostack for aerial robotics. Approach – The TML language combines a task-based hierarchical approach together with a more flexible representation, rule-based reactive planning, to facilitate adaptability. This approach includes additional notions that abstract programming details. We built an interpreter integrated in the software framework Aerostack. The interpreter was validated with flight experiments for multi-robot missions in dynamic environments. Findings – The experiments proved that the TML language is easy to use and expressive enough to formulate adaptive missions in dynamic environments. The experiments also showed that the TML interpreter is efficient to execute multi-robot aerial missions and reusable for different platforms. The TML interpreter is able to verify the mission plan before its execution, which increases robustness and safety, avoiding the execution of certain plans that are not feasible. Originality – One of the main contributions of this work is the availability of a reliable solution to specify aerial mission plans, integrated in an active open-source project with periodic releases. To the best knowledge of the authors, there are not solutions similar to this in other active open-source projects. As additional contributions, TML uses an original combination of representations for adaptive mission plans (i.e., task trees with original abstract notions and rule-based reactive planning) together with the demonstration of its adequacy for aerial robotics. [less ▲]

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See detailHuman-Robot Cooperation in Surface Inspection Aerial Missions
Molina, Martin; Frau, Pedro; Maraval, Dario et al

Scientific Conference (2017, September 21)

The goal of the work presented in this paper is to facilitate the cooperation between human opera- tors and aerial robots to perform surface inspec- tion missions. Our approach is based on a model of ... [more ▼]

The goal of the work presented in this paper is to facilitate the cooperation between human opera- tors and aerial robots to perform surface inspec- tion missions. Our approach is based on a model of human collaborative control with a mixed ini- tiative interaction. In the paper, we present our human-robot cooperation model based on the combination of a supervisory mode and an as- sistance mode with a set of interaction patterns. We developed a software system implementing this interaction model and carried out several real flight experiments that proved that this ap- proach can be used in aerial robotics for sur- face inspection missions (e.g., in vision based indoor missions). Compared to a conventional tele-operated inspection system, the solution pre- sented in this paper gives more autonomy to the aerial systems, reducing the cognitive load of the operator during the mission development. [less ▲]

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See detailVisual Marker based Multi-Sensor Fusion State Estimation
Sanchez Lopez, Jose Luis UL; Arellano-Quintana, Victor; Tognon, Marco et al

in IFAC-PapersOnLine (2017, July), 50(1), 16003-16008

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See detailA flight altitude estimator for multirotor UAVs in dynamic and unstructured indoor environments
Bavle, Hriday; Sanchez Lopez, Jose Luis UL; Rodriguez-Ramos, Alejandro et al

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, June)

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See detailA robust real-time path planner for the collision-free navigation of multirotor aerial robots in dynamic environments
Sanchez Lopez, Jose Luis UL; Pestana, Puerta; Campoy, Pascual

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, June)

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See detailA fully-autonomous aerial robotic solution for the 2016 International Micro Air Vehicle competition
Sampedro, Carlos; Bavle, Hriday; Rodríguez-Ramos, Alejandro et al

in 2017 International Conference on Unmanned Aircraft Systems (ICUAS) (2017, June)

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See detailA reliable open-source system architecture for the fast designing and prototyping of autonomous multi-uav systems: Simulation and experimentation
Sanchez Lopez, Jose Luis UL; Pestana, Jesus; De La Puente, Paloma et al

in Journal of Intelligent and Robotic Systems (2016), 84(1-4), 779-797

During the process of design and development of an autonomous Multi-UAV System, two main problems appear. The first one is the difficulty of designing all the modules and behaviors of the aerial multi ... [more ▼]

During the process of design and development of an autonomous Multi-UAV System, two main problems appear. The first one is the difficulty of designing all the modules and behaviors of the aerial multi-robot system. The second one is the difficulty of having an autonomous prototype of the system for the developers that allows to test the performance of each module even in an early stage of the project. These two problems motivate this paper. A multipurpose system architecture for autonomous multi-UAV platforms is presented. This versatile system architecture can be used by the system designers as a template when developing their own systems. The proposed system architecture is general enough to be used in a wide range of applications, as demonstrated in the paper. This system architecture aims to be a reference for all designers. Additionally, to allow for the fast prototyping of autonomous multi-aerial systems, an Open Source framework based on the previously defined system architecture is introduced. It allows developers to have a flight proven multi-aerial system ready to use, so that they can test their algorithms even in an early stage of the project. The implementation of this framework, introduced in the paper with the name of ``CVG Quadrotor Swarm'', which has also the advantages of being modular and compatible with different aerial platforms, can be found at \url{https://github.com/Vision4UAV/cvg_quadrotor_swarm} with a consistent catalog of available modules. The good performance of this framework is demonstrated in the paper by choosing a basic instance of it and carrying out simulation and experimental tests whose results are summarized and discussed in this paper. [less ▲]

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