Artículos (Ingeniería de Sistemas y Automática)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11342

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Mostrando 1 - 20 de 496

Ensemble speed estimation in IFOC with transient detector
(Wiley, 2025) Arahal, Manuel R.; Garrido Satué, Manuel; Martínez Heredia, Juana María; Perales Esteve, Manuel Ángel; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España
Rotating electric machines have experienced a vast increase in use in recent times due to the electrification of various segments, including electric vehicles. Different machine types, electronic converters, and control schemes are used. In particular, the combination of indirect field oriented control (IFOC) with incremental encoders is widely utilized. Despite theoretical efforts, practical tuning of IFOC-like structures is not easy due to non-idealities. These arise from difficult to model phenomena appearing in the system. In particular, the latency and phase loss of the speed estimation have a negative effect on performance. This paper proposes the use of an ensemble of speed estimators to reduce these negative effects. In the proposal, ripples and latency of the speed estimations are treated as terms in a tradeoff situation. The proposal allows to obtain low ripple in a steady state combined with low latency during transients.
Concurrent AI Tuning of a Double-Loop Controller for Multi-Phase Drives
(MDPI, 2024) Garrido Satué, Manuel; Barrero, Federico; Martínez Heredia, Juana María; Colodro Ruiz, Francisco; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España
The control of electric drives is an important topic due to the wide-spread use of such devices. Among these, multi-phase induction machines are gaining momentum in variable-speed applications. The usual control practice is the use of a speed Proportional–Integral loop that sets the current reference for an inner controller. This inner controller decides the voltage to be applied, which is realized by an electronic power converter. This paper presents an Artificial Intelligence (AI) scheme for tuning. It aims to optimize the usual figures of merit for drives. Moreover, tuning for both loops is tackled concurrently. The adjustment is performed relying on the operating region to address non-linear behavior. The results obtained using a five-phase induction motor illustrate that the proposed method can work in the entire operating range of the drive with improved results.
A Long-Range and Low-Cost Emergency Radio Beacon for Small Drones
(MDPI, 2024) Martínez Heredia, Juana María; Olivera, Jorge; Colodro Ruiz, Francisco; Bravo, Manuel; Arahal, Manuel R.; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España
The increasing use of unmanned aerial vehicles (UAVs) in the commercial and recreational sectors has led to a heightened demand for effective recovery solutions after a crash, particularly for lightweight drones. This paper presents the development of a long-range and low-cost emergency radio beacon designed specifically for small UAVs. Unlike traditional emergency locator transmitters (ELTs), our proposed beacon addresses the unique needs of UAVs by reducing size, weight, and cost, while maximizing range and power efficiency. The device utilizes a global system for mobile (GSM)-based communication module to transmit location data via short message service (SMS), eliminating the need for specialized receivers and expanding the operational range even in obstaclerich environments. Additionally, a built-in global navigation satellite system (GNSS) receiver provides precise coordinates, activated only upon impact detection through an accelerometer, thereby saving power during normal operations. Experimental tests confirm the extended range, high precision, and compatibility of the prototype with common mobile networks. Cost-effective and easy to use, this beacon improves UAV recovery efforts by providing reliable localization data to users in real time, thus safeguarding the UAV investment.
An Improved Speed Sensing Method for Drive Control
(MDPI, 2025) Arahal, Manuel R.; Garrido Satué, Manuel; Martínez Heredia, Juana María; Colodro Ruiz, Francisco; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)
Variable-speed electrical drive control typically relies upon a two-loop scheme, one for torque/speed and another for stator current control. In modern drive control methods, the actual mechanical speed is needed for both loops. In practical applications, the speed is often acquired by incremental rotary encoders. The most used method derives speed from an encoder pulse count during a fixed amount of time. It is known that this sensing method produces time delay in the speed feedback loop as well as fluctuations in the speed measurements. Time lags produce phase loss that has potentially negative effects on the overall drive performance. Nevertheless, the pulse counting method is favored in most cases due to its simplicity and existing support for its use in digital signal processors. In this paper, a new speed sensing method is proposed to reduce time lag without incurring increased fluctuations. The proposal uses a novel transient detector to determine the actual operational regime of the drive: transient or stationary. Transient detection is not based on measured speeds but works directly with the train of incoming encoder pulses. The method is designed to work well with established digital signal processor routines. The proposal is assessed through experimentation on a real five-phase induction motor.
Physical-Virtual Impedance Control in Ultralightweight and Compliant Dual-Arm Aerial Manipulators
(IEEE, 2018-02-26) Suárez Fernández-Miranda, Alejandro; Heredia Benot, Guillermo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Ministerio de Economía y Competitividad (MINECO). España; Ministerio de Educación, Cultura y Deporte (MECD). España; Universidad de Sevilla. TEP151: Robótica, Visión y Control
Dual-arm aerial manipulation requires the design and development of high performance robotic arms in terms of safety, robustness, and force/torque/impedance control, taking into account the integration in the aerial platform, the strong weight constraints, and the technological limitations of the servo actuators. A compliant joint arm also improves the response of the aerial manipulator to collisions and external forces during the flight operation. This letter evaluates the control capabilities in a lightweight manipulator built with smart servo actuators and a spring-lever transmission mechanism that provides joint compliance and deflection measurement. The dynamic model of a compliant joint is validated through frequency identification, demonstrating how virtual variable impedance can be achieved without a second motor. Mechanical joint compliance is the base of the Cartesian impedance control scheme of the dual-arm system, integrated with the controller of the aerial platform. A stereo vision system provides the Cartesian deflection of the end effector, derived from the definition of an equivalent stiff joint manipulator, allowing the estimation and control of the contact forces. Experimental results validate the developed concepts.
Coalitional model predictive control of an irrigation canal
(Elsevier, 2014-04) Fele, Filiberto; Maestre Torreblanca, José María; Hashemy, S. Mehdy; Muñoz de la Peña Sequedo, David; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE); Ministerio de Educación y Cultura (MEC). España
We present a hierarchical control scheme for large-scale systems whose components can exchange information through a data network. The main goal of the supervisory layer is to find the best compromise between control performance and communicational costs by actively modifying the network topology. The actions taken at the supervisory layer alter the control agents’ knowledge of the complete system, and the set of agents with which they can communicate. Each group of linked subsystems, or coalition, is independently controlled through a decentralized model predictive control (MPC) scheme, managed at the bottom layer. Hard constraints on the inputs are imposed, while soft constraints on the states are considered to avoid feasibility issues. The performance of the proposed control scheme is validated on a model of the Dez irrigation canal, implemented on the accurate simulator for water systems SOBEK. Finally, the results are compared with those obtained using a centralized MPC controller.
Coalitional Control: Cooperative Game Theory and Control
(IEEE, 2017-02) Fele, Filiberto; Maestre Torreblanca, José María; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
The evolution of information and communication technologies has yielded the means of sharing measurements and other information in an efficient and flexible way [1], which has enabled the size and complexity of control applications to increase [2]. At the same time, the improvements in the computational and communicational capabilities of control devices have fostered the development of noncentralized control architectures, already motivated by the inherent structural constraints of large-scale systems. Computer-based control approaches such as model predictive control (MPC) are visible beneficiaries of these advances and have registered a significant growth regarding both theoretical and applied fields [3], [4].
Distributed Thermal Identification and Exploitation for Multiple Soaring UAVs
(Springer, 2014-11) Cobano Suárez, José Antonio; Alejo, David; Vera, Santiago; Heredia Benot, Guillermo; Sukkarieh, Salah; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Spagnolo, P.; Mazzeo, P.; Distante, C.; European Commission (EC); Ministerio de Ciencia e Innovación (MICIN). España; Ministerio de Educación, Cultura y Deporte (MECD). España
This chapter discusses the problem of cooperatively sensing the wind map of an area in order to efficiently harvest the wind energy with fixed-wing gliding UAVs, known as soaring. Moreover, a cooperative system with multiple gliding fixed-wing UAVs is presented for long endurance missions. This system is composed by three main blocks that include thermal detector, path planning, and collision avoidance. The main advantage is its low computational load, making it suitable for real-time applications. Extensive simulation results in several scenarios are given to test the complete system. In addition, real experiments have been carried out with real gliding aircrafts of the Robotics Vision and Control Group (GRVC) of the University of Sevilla in the Airfield of La Cartuja (Sevilla). The results of these experiments show the convenience of the proposed method.
Collision-free path planning for multiple robots using efficient turn-angle assignment
(Elsevier, 2024-07) Rodríguez Sánchez, Fabio; Díaz Báñez, José Miguel; Fabila Monroy, Ruy; Caraballo de la Cruz, Luis Evaristo; Capitán Fernández, Jesús; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Union NextGeneration; Universidad de Sevilla. TEP995: Multi-robot And Control Systems
The ability to avoid collisions with moving robots is critical in many applications. Moreover, if the robots have limited battery life, the goal is not only to avoid collisions but also to design efficient trajectories in terms of energy consumption and total mission time. This paper proposes a novel strategy for assigning turn angles for collision-free path planning in scenarios where a small team of robots cooperate in a certain mission. The algorithm allows each robot to reach a predetermined destination safely. It establishes consecutive, short time intervals, and at each interval, possible conflicts are solved centrally in an optimal manner. This is done by keeping constant speeds but generating a discrete set of possible directions for each robot, and solving efficiently the turn-angle allocation for a collision-free path that minimizes the path deviation from the shortest one. Due to the discretization, the final paths are not optimal, but the system can react to possible failures during execution, as conflicts are resolved at each time interval. Computational results and Software-In-The-Loop simulations are presented in order to evaluate the proposed algorithm. A comparison with a state-of-the-art approach shows that our algorithm is more energy-efficient and achieves lower mission completion time.
Autonomous Aerial Filming with Distributed Lighting by a Team of Unmanned Aerial Vehicles
(Institute of Electrical and Electronics Engineers (IEEE), 2021-10) Kratky, Vit; Alcántara Marín, Alfonso; Capitán Fernández, Jesús; Stepan, Petr; Saska, Martin; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Junta de Andalucía
This letter describes a method for autonomous aerial cinematography with distributed lighting by a team of unmanned aerial vehicles (UAVs). Although camera-carrying multi-rotor helicopters have become commonplace in cinematography, their usage is limited to scenarios with sufficient natural light or of lighting provided by static artificial lights. We propose to use a formation of unmanned aerial vehicles as a tool for filming a target under illumination from various directions, which is one of the fundamental techniques of traditional cinematography. We decompose the multi-UAV trajectory optimization problem to tackle non-linear cinematographic aspects and obstacle avoidance at separate stages, which allows us to re-plan in real time and react to changes in dynamic environments. The performance of our method has been evaluated in realistic simulation scenarios and field experiments, where we show how it increases the quality of the shots and that it is capable of planning safe trajectories even in cluttered environments
A Dynamic Weighted Area Assignment Based on a Particle Filter for Active Cooperative Perception
(Institute of Electrical and Electronics Engineers (IEEE), 2020-04) Acevedo Báñez, José Joaquín; Messias, Joao; Capitán Fernández, Jesús; Ventura, Rodrigo; Merino, Luis; Lima, Pedro U.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; Universidade de Lisboa; Universidad de Sevilla. TEP151: Robótica, Visión y Control
This article addresses an Active cooperative perception problem for networked robots systems. Given a team of networked robots, the goal is finding a target using their inherent uncertain sensor data. The article proposes a particle filter to model the probability distribution of the position of the target, which is updated using detection measurements from all robots. Then, an information-theoretic approach based on the RRT∗ algorithm is used to determine the optimal robots trajectories that maximize the information gain while surveying the map. Finally, a dynamic area weighted allocation approach based on particle distribution and coordination variables is proposed to coordinate the networked robots in order to cooperate efficiently in this active perception problem. Simulated and real experimental results are provided to analyze, evaluate and validate the proposed approach.
The Velocity Assignment Problem for Conflict Resolution with Multiple Aerial Vehicles Sharing Airspace
(Springer, 2013-01) Alejo, David; Díaz Báñez, José Miguel; Cobano Suárez, José Antonio; Pérez Lantero, Pablo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP151: Robótica, Visión y Control
Efficient conflict resolution methods for multiple aerial vehicles sharing airspace are presented. The problem of assigning a velocity profile to each aerial vehicle in real time, such that the separation between them is greater than a given safety distance, is considered and the total deviation from the initial planned trajectory is minimized. The proposed methods involve the use of appropriate airspace discretization. In the paper it is demonstrated that this aerial vehicle velocity assignment problem is NP-hard. Then, the paper presents three different collision detection and resolution methods based on speed planning. The paper also presents simulations and studies for several scenarios.
Conflict Detection and Resolution Method for Cooperating Unmanned Aerial Vehicles
(2012-01) Conde, Roberto; Alejo, David; Cobano Suárez, José Antonio; Viguria, Antidio; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Junta de Andalucía; Univarsidad de Sevilla. TEP151; Robotica, Vision y Control
This paper presents a Conflict Detection and Resolution (CDR) method for cooperating Unmanned Aerial Vehicles (UAVs) sharing airspace. The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost. The method changes the initial flight plan of each UAV by adding intermediate waypoints that define the solution flight plan while maintaining their velocities. The method has been validated with many simulations and experimental results with multiple aerial vehicles platforms based on quadrotors in a common airspace. The experiments have been carried out in the multi-UAV aerial testbed of the Center for Advanced Aerospace Technologies (CATEC).
Human Modeling and Passivity Analysis for Semi-Autonomous Multi-Robot Navigation in Three Dimensions
(Institute of Electrical and Electronics Engineers (IEEE), 2024) Hatanaka, Takeshi; Mochizuki, Takahiro; Sumino, Takumi; Maestre Torreblanca, José María; Chopra, Nikhil; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
In this article, we study a one-human-multiple-robot interaction for human-enabled multi-robot navigation in three dimensions. We employ two fully distributed control architectures designed based on human passivity and human passivity shortage. The first half of this article focuses on human modeling and analysis for the passivity-based control architecture through human operation data on a 3-D human-in-the-loop simulator. Specifically, we compare virtual reality (VR) interfaces with a traditional interface, and examine the impacts that VR technology has on human properties in terms of model accuracy, performance, passivity and workload, demonstrating that VR interfaces have a positive effect on all aspects. In contrast to 1-D operation, we confirm that operators hardly attain passivity regardless of the network structure, even with the VR interfaces. We thus take the passivity-shortage-based control architecture and analyze the degree of passivity shortage. We then observe through user studies that operators tend to meet the degree of shortage needed to prove closed-loop stability.
Stochastic Optimization of Microgrids with Hybrid Energy Storage Systems for Grid Flexibility Services Considering Energy Forecast Uncertainties
(Institute of Electrical and Electronics Engineers (IEEE), 2021-11) García Torres, Félix; Bordons Alba, Carlos; Tobajas, Javier; Real-Calvo, Rafael; Santiago, Isabel; Grieu, Stephane; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
This paper presents a stochastic framework for the optimization of microgrids that has the functionality of providing flexibility services to System Operators (SOs) considering uncertainties in the energy forecast. The methodology is developed with the aim of being applied to complex microgrids composed of different distributed energy resources and hybrid energy storage systems (ESS). The associated optimization problem is operated in two stages: the first one performs a stochastic optimization of the microgrid in order to reserve an up/down regulation capacity with which to deal with the energy forecast uncertainties of the microgrid. The different microgrid devices are optimized by considering their operational costs in order to achieve their optimal operation in the Day-Ahead Market (DM). The second stage is used to re-schedule the initial planning according to the signal request and an economic offer from the SO. The control problem is developed using Stochastic Model Predictive Control (SMPC) techniques and Mixed-Integer Quadratic Programming (MIQP), owing to the presence of logic, integer, mixed and probabilistic variables. The simulation results show that the proposed methodology reduces the risk of undergoing up/down-penalty deviations in the Regulation Service Market (RM), also being able to provide flexibility services to the SOs, despite being subject to uncertainties in the energy forecast carried out for the microgrid.
Chance Constraints and Machine Learning integration for uncertainty management in Virtual Power Plants operating in simultaneous energy markets
(Elsevier, 2021-12) Aguilar, Juan; Bordons Alba, Carlos; Arce, Alicia; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
The management of uncertainty is one of the most important issues affecting the optimal operation of Distributed Energy Resources (DERs). Virtual Power Plants (VPPs) aggregate different Energy Nodes (ENs) to enable them to participate in energy markets in an aggregated way. This participation requires very accurate forecast services to trade off between the revenue at bidding time, by making more aggresive bids, and the reduction of penalties at operation time due to deviations from the commitment. In this paper, a stochastic optimization layer is built over a Model Predictive Control (MPC) kernel to define a Stochastic Model Predictive Control (SMPC) scheme by combining Chance-Constrained (CC) and Machine Learning (ML) to handle the uncertainty related to generation and load profiles at optimization time.This technique can be applied to participate simultaneously in different energy markets depending on the configuration or capacity of the VPP, and according to the business model of the system operator. More accurate optimizations allow more profitable operations and more flexibility to redistribute the energy allocation to offer different energy services. The results are satisfactory as this scheme works better than the deterministic approach in terms of penalty reduction for most of the cases.
Voronoi Multi-phase Predictive Current Control with Variable Application Times
(IEEE, 2025) Arahal, Manuel R.; Barrero, Federico; Garrido Satué, Manuel; Colodro Ruiz, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Agencia Estatal de Investigación. España
Predictive Stator Current Control (PSCC) is a flexible technique for drives of different types. For the multiphase case, PSCC must deal with an increased number of available control options (the voltage vectors) and cope with the different current spaces: torque producing (α−β) and harmonic planes (x − y). In this paper, a Voronoi region based scheme is designed to cope with both issues while maintaining an affordable commutation frequency. The proposal is enhanced by using variable application times with fine resolution. The method is compared with state of the art dead-beat multi-vector approach. The comparison is made using a real, laboratory setup designed for experimentation based on a five-phase induction machine. The comparison shows enhanced control results together with a reduction in harmonic content, without compromising the switching frequency limits of the power converters and maintaining flexibility due to the cost function.
Robust Model Predictive Control for an Ion Beam Shepherd in a large-debris removal mission
(Elsevier, 2024-12) Urrios Gómez, Francisco Javier; Vázquez Valenzuela, Rafael; Gavilán Jiménez, Francisco; Alvarado Aldea, Ignacio; Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; European Union (UE)
The increasing accumulation of space debris poses significant risks to spacecraft, making the development of effective debris mitigation technologies necessary. This paper explores the Ion Beam Shepherd (IBS) method as a potential contactless solution for deorbiting large debris objects. The IBS system concept involves a spacecraft equipped with an ion thruster to direct a controlled ion beam at the debris, generating a small force that gradually lowers its orbit. A proposed configuration of the chaser’s actuator system integrates radial and out-of-plane cold-gas thrusters along with in-track ion thrusters to enhance control and safety while maintaining low mission costs. A robust Model Predictive Control (MPC) strategy is implemented, using the theory of MPC for Tracking to ensure accurate positioning and effective deorbiting. This theoretical approach addresses uncertainties and perturbations to robustly guarantee safe distances between the chaser and the debris. Additionally, a new ray-marching-based algorithm is introduced to estimate the force and torque exerted by the ion beam on the target, considered as a 6 degrees of freedom object, improving simulation accuracy and control performance assessment. A comprehensive simulation of the deorbit of a large debris object is performed, demonstrating the potential of the IBS technology for future large-debris removal missions. This research advances the conceptual framework and control techniques for the IBS technology, advancing towards its future implementation in space debris mitigation.
Multi-Phase Stator Current Tracking with Gradual Penalization of Commutations
(MDPI, 2024-07) Arahal, Manuel R.; Garrido Satué, Manuel; Martínez Heredia, Juana María; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica
Energy efficiency in drives is an important issue. In converter-supplied variable-speed drives, switching losses can amount to a significant portion of all losses. This has been considered in Predictive Stator Current Control (PSCC), considering commutations at the power converter. However, in multi-phase drives, the computational burden limits the application of said techniques. Recent fast predictive algorithms have enabled shorter application times with enhanced tracking results. However, the switching frequency becomes larger with diminishing sampling periods. This paper presents a method that retains the fast computation of recent methods while reducing the switching frequency. The proposal revolves around a modification of the cost function to penalize commutations in a nonlinear way. For this task, a novel, gradual penalization is introduced. The method is experimentally applied to a five-phase induction motor. Experimental results show a significant reduction in switching frequency without compromising other control objectives. This results in an enhanced PSCC with a small sampling period and reduced switching losses.
Collision-Free 4D Trajectory Planning in Unmanned Aerial Vehicles for Assembly and Structure Construction
(Springer, 2014-01) Alejo, David; Cobano Suárez, José Antonio; Heredia Benot, Guillermo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Ministerio de Ciencia e Innovación (MICIN). España; Junta de Andalucía; Universidad de Sevilla. TEP151: Robótica, Visión y Control
This paper presents a new system for assembly and structure construction with multiple Unmanned Aerial Vehicles (UAVs) which automatically identifies conflicts among them. The system proposes the most effective solution considering the available computation time. After detecting conflicts between UAVs, the system resolves them cooperatively using a collision-free 4D trajectory planning algorithm based on a simple one-at-a-time strategy to quickly compute a feasible but non-optimal initial solution and a stochastic optimization technique named Particle Swarm Optimization (PSO) to improve the initial solution. An anytime approach using PSO is applied. It yields trajectories whose quality improves when available computation time increases. Thus, the method could be applied in real-time depending on the available computation time. The method has been validated with simulations in scenarios with multiple UAVs in a common workspace and experiment in an indoor testbed.

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