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This paper is about an application of a method based on the ECIES (Elliptic Curve Integrated Encryption Scheme) to improve the security against malicious attacks of the UAVs (Unmanned Aerial Vehicles) communications system. This system is focused on improving the security conditions in extreme situations and preventing the aircraft for man-made incidents and cyber attacks. The paper briefly describes the different attacks that can affect to the operation of UAVs and the security methods that, nowadays, are used to guarantee the security during the operations. Moreover, it presents a solution to a strong vulnerability detected in the classical scheme used in UAV. This scheme uses ROS (Robot Operating System) as the core of the communication system to interconnect different devices and nodes in this paper, it is demonstrated that if an Intruder is able to enter in the local network of the UAV system, he/she is also able to impersonate the GCS (Ground Control Station) of the UAV and take control of it leading to an undesirable maneuver or even a dangerous crash against a building or a person. The security system proposed to avoid this consists of a simplified method based on ECIES sending packets, between UAV and GCS, which uses ECDSA (Elliptic Curve Digital Signature) and are ciphered in RSA (Rivest–Shamir–Adleman). Thus, it is possible to guarantee that the high level computer of the UAV is able to identify the identity of their GCS and prevent of being commanded by an unauthorized Intruder. Both, the vulnerability and the solution proposed have been experimentally tested and validated through software-in-the-loop simulations and in a outdoor scenario using a small UAV.

This paper presents a robotic system using Unmanned Aerial Vehicles (UAVs) for bridge-inspection tasks that require physical contact between the aerial platform and the bridge surfaces, such as beam-deflection analysis or measuring crack depth with an ultrasonic sensor. The proposed system takes advantage of the aerodynamic ceiling effect that arises when the multirotor gets close to the bridge surface. Moreover, this paper describes how a UAV can be used as a sensor that is able to fly and touch the bridge to take measurements during an inspection by contact. A practical application of the system involving the measurement of a bridge&rsquo, s beam deflection using a laser tracking station is also presented. In order to validate our system, experiments on two different bridges involving the measurement of the deflection of their beams are shown.

Winged aerial robots represent an evolution of aerial manipulation robots, replacing the multirotor vehicles by fixed or flapping wingplatforms. The development of this morphology is motivated in terms of efficiency, endurance and safety in some inspection operations where multirotor platforms may not be suitable. This paper presents a first prototype of compliant dual arm as preliminary step towards the realization of a winged aerial robot capable of perching and manipulating with the wings folded. The dual arm provides 6 DOF (degrees of freedom) for end effector positioning in a human-like kinematic configuration, with a reach of 25 cm (half-scale w.r.t. the human arm), and 0.2 kg weight. The prototype is built with micro metal gear motors, measuring the joint angles and the deflection with small potentiometers. The paper covers the design, electronics, modeling and control of the arms. Experimental results in test-bench validate the developed prototype and its functionalities, including joint position and torque control, bimanual grasping, the dynamic equilibrium with the tail, and the generation of 3D maps with laser sensors attached at the arms.

This paper proposes the application of long reach manipulators (LRM) in aerial manipulation, attaching a human size and lightweight dual arm at the tip of a flexible link installed at the base of the aerial platform. This configuration extends the reach and the volume of operation of the manipulator, whose workspace is constrained by the propellers and the landing gear, increasing also safety during the physical interactions on flight between the aerial robot and the environment. The deflection of the flexible link is exploited for collision detection and obstacle localization, allowing also the control of the contact force exerted by the arms. These capabilities are supported by a vision system that measures the deflection at the tip. Undesired oscillations of the link are suppressed generating a coordinated motion with the arms. Experiments in a fixed base test bench are conducted for validating the developed functionalities.

This paper presents an anthropomorphic, compliant and lightweight dual arm manipulator designed and developed for aerial manipulation applications with multi-rotor platforms. Each arm provides four degrees of freedom in a human-like kinematic conguration for end effector positioning: shoulder pitch, roll and yaw, and elbow pitch. The dual arm, weighting 1.3 kg in total, employs smart servo actuators and a customized and carefully designed aluminum frame structure manufactured by laser cut. The proposed design reduces the manufacturing cost as no computer numerical control machined part is used. Mechanical joint compliance is provided in all the joints, introducing a compact spring-lever transmission mechanism between the servo shaft and the links, integrating a potentiometer for measuring the deection of the joints. The servo actuators are partially or fully isolated against impacts and overloads thanks to the ange bearings attached to the frame structure that support the rotation of the links and the detection of the joints. This simple mechanism increases the robustness of the arms and safety in the physical interactions between the aerial robot and the environment. The developed manipulator has been validated through different experiments in xed base test-bench and in outdoor ight tests.

This paper presents the development and experimental validation of a low weight and inertia, human-size and highly dexterous dual arm system designed for aerial manipulation with multirotor platform. The arms, weighting 1.8 kg in total and with a maximum lift load per arm around 0.75 kg, provide five degrees of freedom (DOF) forend-effectorpositioning and wrist orientation. A customized aluminum frame structure supports the servo actuators, placing most part of the mass close to the shoulder structure in order to reduce the inertia. A doubleflangebearing mechanism in side-by-side configuration isolates the servos from impacts and radial/axial overloads, increasing robustness. This is important to prevent that the arms are damaged during physical interactions with the environment, as they should support thekineticenergy of the whole platform. The motivation in the development of a dual arm aerial manipulator is extending the range of applications and tasks that can be performed with respect to the single arm case, like grasping large objects or assembling. The paper covers the kinematic and dynamic modeling of the aerial robot, proposing a control scheme that deals with the technological limitations of the smart servo actuators. The performance of the arms and the interactions with the aerial platform are evaluated intest benchexperiments. The proposed dual arm design is validated through outdoor flight tests with two commercial hexarotor platforms equipped with standard industrialautopilots.

This article deals with aerial manipulators consisting of unmanned helicopters equipped with robotic multi-link arms. This setup has strong potentialities for structure assembly and manipulation tasks, which makes it a valuable resource in outdoor industrial environments. The article presents an elaborate model of the entire system as well as methods for controlling the aerial platform taking into account the motion of the arm. The article presents the design and implementation of a Variable Parameter Integral Backstepping controller which clearly outperforms the results obtained with the standard helicopter controller. Realistic characterization of system sensors has been also accounted for. Simulations experiments confirm the validity of the proposed approach, and the results are also validated with a high-fidelity Modelica simulation model.

The proximity between the multirotor blades and the environmental obstacles restricts the application of aerial manipulators in inspection tasks due to the risk of impacts, the limitation in the reach of the arm, and the physical interactions. This paper presents a long reach aerial manipulator consisting of a hexarotor platform equipped with a 2-DOF compliant joint arm attached at the tip of a one-meter-length link in passive pendulum configuration. The arm integrates magnetic encoders for force/torque estimation-control based on joint deflection, a range sensor in the forearm link for measuring the distance to the contact point, and a camera for visual inspection. A 2-DOF wearable exoskeleton interface has been developed, allowing the teleoperation of the arm with visual feedback in a more intuitive way. The paper also covers the kinematics and dynamics of the aerial manipulator, including the dynamics of the flexible long reach link. The developed system has been evaluated in testbench and in outdoor flight tests.

This paper considers the problem of fault detection and identification (FDI) in applications carried out by a group of unmanned aerial vehicles (UAVs) with visual cameras. In many cases, the UAVs have cameras mounted onboard for other applications, and these cameras can be used as bearing-only sensors to estimate the relative orientation of another UAV. The idea is to exploit the redundant information provided by these sensors onboard each of the UAVs to increase safety and reliability, detecting faults on UAV internal sensors that cannot be detected by the UAVs themselves. Fault detection is based on the generation of residuals which compare the expected position of a UAV, considered as target, with the measurements taken by one or more UAVs acting as observers that are tracking the target UAV with their cameras. Depending on the available number of observers and the way they are used, a set of strategies and policies for fault detection are defined. When the target UAV is being visually tracked by two or more observers, it is possible to obtain an estimation of its 3D position that could replace damaged sensors. Accuracy and reliability of this vision-based cooperative virtual sensor (CVS) have been evaluated experimentally in a multivehicle indoor testbed with quadrotors, injecting faults on data to validate the proposed fault detection methods. Comisión Europea H2020 644271 Comisión Europea FP7 288082 Ministerio de Economia, Industria y Competitividad DPI2015-71524-R Ministerio de Economia, Industria y Competitividad DPI2014-5983-C2-1-R Ministerio de Educación, Cultura y Deporte FPU

Este artículo presenta el primer robot manipulador aéreo con dos brazos antropomórficos diseñado para aplicarse en tareas de inspección y mantenimiento en entornos industriales de difícil acceso para operarios humanos. El robot consiste en una plataforma aérea multirrotor equipada con dos brazos antropomórficos ultraligeros, así como el sistema de control integrado de la plataforma y los brazos. Una de las principales características del manipulador es la flexibilidad mecánica proporcionada en todas las articulaciones, lo que aumenta la seguridad en las interacciones físicas con el entorno y la protección del propio robot. Para ello se ha introducido un compacto y simple mecanismo de transmisión por muelle entre el eje del servo y el enlace de salida. La estructura en aluminio de los brazos ha sido cuidadosamente diseñada de forma que los actuadores estén aislados frente a cargas radiales y axiales que los puedan dañar. El manipulador desarrollado ha sido validado a través de experimentos en base fija y en pruebas de vuelo en exteriores.

The inspection of bridges and other infrastructure with UAVs when the sensors need to be in contact with the surface (i.e. ultrasound for crack inspection or reflector prism for beam deflection) is a great challenge due to the coupling which occurs between the aerial and the inspection problems. This paper presents a new design of a multirotor UAV that can be used in some of these applications to eliminate the coupling and to be able to carry out the inspection by contact in a more effective way. The proposed solution uses the so-called ceiling effect to maintain in contact a specially designed aerial platform to the ceiling. So, the coupling disappears because the multirotor is still in contact with the ceiling in a fixed position while performing inspection. Moreover, the presented results show that making use of the ceiling effect also improved the maximum flight time of the platform. The solution is presented with experimental results in a test stand and flight tests representing a bridge inspection application (Fig. 1). A video of the experiments is also included.

This paper analyzes the ground effect in multirotors, that is, the change in the thrust generated by the rotors when flying close to the ground due to the interaction of the rotor airflow with the ground surface. This effect is well known in single-rotor helicopters but has been assumed erroneously to be similar for multirotors in many cases in the literature. In this paper, the ground effect for multirotors is characterized with experimental tests in several cases and the partial ground effect, a situation in which one or some of the rotors of the multirotor (but not all) are under the ground effect, is also characterized. The influence of the different cases of ground effect in multirotor control is then studied with several control approaches in simulation and validated with experiments in a test bench and with outdoor flights. European Commission H2020-2014-644271 Ministerio de Economía y Competitividad DPI2014-59383-C2-1-R, DPI2015-71524-R

This paper presents a collision-free trajectory planner to perform applications of WSN (Wireless Sensor Network) data collection in dynamic environments with Unmanned Aerial Vehicles. The missions are given by a set of waypoints which define WSN collection zones and each UAV should pass through these zones to collect the data. Therefore, two planners based on RRT (Rapidly-exploring Random Trees) and RRT * (Optimal Rapidly-exploring Random Trees) planning algorithms have been implemented. These planners compute trajectories between WSN collection zones to ensure that the UAV passes through the WSN collection zones. Simulations and experiments carried out in the airfield of Utrera (Seville, Spain) show the performance and advantages of the proposed algorithm.

This paper presents an advanced model and control structure of a non-linear hybrid system: a gasoline direct injection (GDI) engine. The engine management system proposed in the paper is based on a hierarchical structure that uses Takagi—Sugeno fuzzy models of the engine to define piecewise linear controllers. Thanks to the hierarchical controller structure, engine idle speed regulation is tackled as a high-level requirement and therefore no specific low-level controller is needed. Moreover, the two combustion modes are correctly handled to optimize the engine efficiency. A global stability analysis of the GDI engine working either in homogeneous mode or in stratified mode is also presented, based on bifurcation analysis. Bifurcation analysis can be applied to a wide range of different controllers (even close-to-production), and therefore it can be of significant practical value.

This paper presents a method to increase the reliability of UAV sensor fault detection in a multi- UAV context. The method uses additional position estimations that augment individual UAV fault detection system. These additional estimations are obtained using images from the same planar scene taken from two different UAVs. Since accuracy and noise level of the estimation depends on several factors, dynamic replanning of the multiUAV team can be used to obtain a better estimation in case of faults caused by slow growing errors of absolute position estimation that cannot be detected by using local FDI in the UAVs. Experimental results with data from two real UAVs are also presented.

[Resumen] En este artículo se describen los primeros robots manipuladores aéreos dotados con brazos robóticos de seis grados de libertad y capacidades de percepción y planificación que se han desarrollado en el mundo. Estos robots son el resultado del proyecto ARCAS (Aerial Robotics Cooperative Assembly System) coordinado por el primero de los autores y financiado por el Séptimo Programa Marco de la Unión Europea. Los resultados de este proyecto han comenzado a emplearse, entre otros, en el proyecto H2020 AEROARMS y en el español AEROMAIN. El artículo introduce las diferentes plataformas utilizadas en el proyecto y a continuación resume las principales características de los sistemas de control, percepción y planificación desarrollados. Se resume también la integración y validación del sistema. Este trabajo ha sido financiado parcialmente por el Proyecto Europeo del FP7 ARCAS (ICT-2011-287617) y por el H2020 AEROARMS (ICT-23-2014-644271), así como por el proyecto nacional AEROMAIN DPI2014-59383-C2-1-R del Ministerio de Economía y Competitividad https://doi.org/10.17979/spudc.9788497498081

This chapter focuses on the optimal trajectory generation for multiple autonomous vehicles. Nowadays, there are many outdoor and indoor applications where teams of robots and unmanned vehicles are very useful. In these cases the ability of autonomous navigation and adaptive motion control is given by trajectory planning methods. Furthermore, trajectory planning methods are very important in cooperative applications. A subset of trajectory planning methods focus on finding the optimal solution given by a specific criterion. A constrained problem has to be solved when two or more vehicles share the same space in a multiple vehicle application. We present a new optimal trajectory planning method based on pseudospectral collocation methods, which are especially suitable for multivehicle problems. Pseudospectral collocation methods are based on the solving of numerically optimal control problems by effective discretization and conversion to an algebraic nonlinear programming problem, which can be efficiently solved by application of optimization tools. We consider several kinds of applications and scenarios with multiple aerial and ground vehicles. Experimental results with teams of unmanned aerial vehicles and unmanned ground vehicles are provided to validate the multivehicle trajectories obtained by the methods.

Increasing flight endurance of Unmanned Aerial Vehicles (UAVs) is a main issue for many applications of these aircrafts. This paper deals with air to air refueling between UAVs. Relative estimation using only INS/GPS system is not sufficiently accurate to accomplish an autonomous dock for aerial refueling. In this paper we propose a relative state estimator to fuse GPS and INS sensor data of each UAV with vision pose estimation of the receiver obtained from the tanker and serves as an introduction to fault detection in autonomous aerial refueling comparing vision and INS measurements. Simulated results validate the fault detection indicator and are the starting point for ground and flight tests in the next months.

This paper presents an aerial manipulator consisting of a multirotor equipped with a robotic multi-link arm attached to the top of the multirotor body. This setup has strong potentialities for inspection of structures, since the arm is able to safely touching the structure surface with a sensor while flying, taking measurements from the underside for example in bridges. The paper presents the dynamic model of the system and the derivation of a nonlinear controller, which is tested in simulation. First flight experiments with prototype of the system are also presented.

This paper presents a system for collision-free trajectory planning with multiple Unmanned Aerial Vehicles (UAVs) which automatically identifies conflicts among them. After detecting conflicts between UAVs, the system resolves them cooperatively using a collision-free trajectory planning algorithm based on a stochastic optimization technique named Particle Swarm Optimization (PSO). The new implementation of the PSO algorithm, named Maneuver Selection Particle Swarm Optimization (MS-PSO), presents improvements with respect to previous implementations. The execution time is reduced because the dimension of the problem is reduced, and different kinds of maneuvers can be selected to solve the detected conflicts: course/heading, speed or altitude changes. The MS-PSO has been validated with simulations in scenarios with multiple UAVs in a common airspace. Also, a comparison to a genetic algorithm and a PSO algorithm has been performed to highlight the advantages of the MS-PSO. The main advantage is that MS-PSO always ensures solution from the first iteration. This requirement is essential in safe cooperative missions.

This paper presents a Ground Control Station based on the Robot Operating System (ROS) which has been developed in order to monitor highly automated multi-UAV missions. The proposed system has been designed in order to easily perform Hardware in the Loop (HIL) simulations. This allows to test the desired algorithms in an environment as close as possible to the one found in real experimentation, which will reduce the costs related to field experiments. The architecture of the system is fully based on open source software, protocols and hardware. Furthermore a new user interface has been developed in order to provide relevant information in multi-UAV gliding experiments. This tool allows the operator to allocate tasks to the UAV and to monitor the operational information. This information can be complemented with the use of open source control stations. The proposed system has been demonstrated in both HIL simulation and in field experimentation. These results are compared in order to indicate how close the simulated behaviour was with respect to the real.

This paper presents a Guidance, Navigation and Control (GNC) system for the autonomous landing of a Remotely Piloted Aircraft Helicopter (RPAS) in a GPS-denied scenario by using a tether in the landing. A new control and sensor fusion strategy has been designed for landing accurately by means of relative position and velocity commands. The system uses on-board the RPAS a device with a cardan joint providing the angles between the tether and the helicopter frame and a force sensor giving the tension of the tether.

This paper presents an optimal conflict resolution method for multiple unmanned aerial vehicles based on pseudospectral collocation which solves numerically optimal control problems by using non-linear programming. The trajectory of each aerial vehicle is defined by a set of waypoints and the time of arrival at each waypoint. The maneuvers allowed to solve the conflicts are the changes of speed of each aerial vehicle. A novel aspect is the application of this kind of methods to multiple aerial vehicles. The main characteristic of the method is the low execution time in the addressed problem. Moreover, the scalability of the proposed method is studied and the execution time is compared with another optimal solver. Several simulations in different scenarios are performed to test the behavior of the method.

This paper proposes a method called Segmentation-adaptive Pseudospectral collocation to address the problem of safe trajectory generation in missions with cooperating multiple aerial vehicles. Pseudospectral collocation can generate optimized collision-free trajectories, but for multiple aerial vehicles it cannot guarantee that the safety separation distance is maintained in the whole trajectories, since the constraints are only enforced in discrete points in the trajectory (collocation points). Hp-adaptive pseudospectral collocation increases iteratively the number of collocation points and the degree of the approximating polynomial, but this may lead to an exponential increase of the computational load. The proposed method solves the problem by selectively adding new collocation points where they are needed, only in the segments with conflicts in each iteration, thus effectively reducing the number of collocation points and the computation time with respect to other pseudospectral collocation formulations. The proposed method allows both changes of speed and changes of heading for each aerial vehicle to guarantee the safety distance between them. Its computational load and scalability are studied in randomly generated scenarios. Moreover, a comparison with other method is presented. Several experiments to test the validity of the approach have been also carried out in the multivehicle aerial testbed of the

This paper presents a conflict resolution method in converging air traffic based on an hp-adaptative pseudospectral method. The technique generates conflict free trajectories in scenarios with multiple aircraft. This method computes an optimal solution numerically. It assigns a speed profile to each aircraft sequencing the order of arrival to the TMA entry point such that the separation between them is greater than a minimum safety distance and the total deviation from the initial trajectories is minimized. The paper also presents simulations in converging scenarios by considering unlocked and locked aircraft.

This paper presents a collision avoidance algorithm for multiple aerial vehicle systems to be applied in real-time. The proposed algorithm is based on the 3D-Optimal Reciprocal Collision Avoidance (ORCA) algorithm. Several improvements have been implemented such as considering dynamic constraints of the UAV model and static obstacles, so it can be used in realistic environments. The algorithm has been integrated in ROS framework and tested with up to eight Unmanned Aerial Vehicles (UAVs). Several simulations in a realistic environment have been performed, including long endurance cooperative missions. A comparison with the ORCA algorithm is presented to analyze the improvements done.

This paper presents an advanced control structure and its simulation environment for a non-linear hybrid system: a GDI engine. The engine management system proposed is based on a hierarchical structure that uses fuzzy models of the engine to define piecewise linear controllers. A stability analysis of the GDI engine based on bifurcation diagrams is also presented.

This paper studies a fuzzy-supervised path tracking system designed and implemented for driving large unmanned vehicles at high speed. Thus, reliability and high performance are very important issues. The control system has two main functions: vehicle position estimation and generation of the steering commands for the vehicle to follow a given path autonomously. Position estimation is based on a differential OPS system with additional functions to improve the reliability. In fact, the highly demanding navigation conditions impose strict requirements on the dynamic behavior. This paper presents a frequency response analysis of the control loop. The results of this analysis correspond to the obtained experimentally with a truck circulating by testing tracks.

This paper studies the stability of fuzzy path tracking of autonomous vehicles. This problem lies in the generation of the steering commands for a vehicle to follow a given path autonomously. In this control loop, both the plant and the fuzzy controller are nonlinear. Due to this nonlinearity, complex behavioral phenomena can occur, giving rise to the loss of global stability. The extension of conventional frequency response methods for the stability analysis of the nonlinear fuzzy path-tracking control loop is proposed. Simulation experiments show the validity of the proposed method in three different cases: stable origin and unstable limit cycle, delay-induced Hopf bifurcation, and delay-induced unstable limit cycle.

This paper presents the most significant components in the control architecture of the ROMEO outdoor autonomous vehicles. A short description of the general characteristics of the ROMEO-3R (tricycle) and ROMEO-4R (four wheels) vehicles is included. These autonomous vehicles are the result of the adaptation of conventional electric vehicles and they are currently used for experimentation in autonomous navigation and teleoperation in outdoor environments. The paper presents the general characteristics of the vehicles and the control architecture. Then describes the position estimation and the tracking components. The former components include: position estimation using dead reckoning sensors and orientation sensors, global position estimation using GPS, and position estimation with respect to the environment. On the other hand, tracking components include: tracking of explicit paths, moving objects, and environment features.

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.

This paper studies the stability of closed loop systems with a fuzzy logic controller. The method presented considers explicitly the global state-space stability of the system, in situations where multiple steady regimes are involved. The stability analysis is applied to the direct fuzzy path tracking of autonomous vehicles. This problem consist in the generation of the steering commands for a vehicle to follow autonomously a given path. In this control loop both the plant to be controlled and the fuzzy controller are non-linear. Due to this nonlinearity complex behavior phenomena can occur giving rise to the loss of the global stability. The extension of conventional frequency response method for the stability analysis of the nonlinear fuzzy path tracking control loop is proposed. Simulations experiments show the validity of the proposed method in three different cases, stable origin and unstable limit cycle, delay-induced Hopf bifurcation, and delay-induced unstable limit cycle.

This paper presents a cooperative system architecture that extends the flight duration of multiple gliding fixed-wing Unmanned Aerial Vehicles (UAVs) for long endurance missions. The missions are defined by a set of Points of Interest (PoI) and UAVs should pass through them. A module to detect and identify thermals is implemented to exploit their energy and extend the flight duration, known as static soaring. A collision-free trajectory planner based on the RRT* (Optimal Rapidly-exploring Random Trees) planning algorithm is implemented. The proposed system allows applications in real time because of its low computational needs. Simulations and experiments carried out in the airfield of La Cartuja (Seville, Spain) show the performance and advantages of the proposed system.

This paper addresses the problem of extending the flight duration of cooperative missions with multiple gliding fixed-wing UAVs by using the energy that comes from static soaring. We consider exploration missions where UAVs should pass through a set of Point of Interest (PoI) with the presence of thermals in the space. These thermals can be exploited to provide energy in terms of altitude for each gliding UAV. The objective of the mission is to extend the flight duration of each UAV to explore the environment without landing and decreasing the time to perform the mission. An algorithm named Bounded Recursive Heuristic Search (BRHS), based on Depth-First search techniques, is applied to the PoIs and to the UAVs. The main advantage is the real time application because of the low computational load. The paper presents a set of simulations and experiments have carried out in the airfield of La Cartuja (Seville, Spain).

This paper presents a new system which automatically identifies conflicts between multiple UAVs (Unmanned Aerial Vehicles) and proposes the most effective solution considering the available computation time. The system detects conflicts using an algorithm based on axis-aligned minimum bounding box and resolves them cooperatively using a collision-free 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. PSO modifies the 4D trajectories of the UAVs with an overall minimum cost. Determining optimal trajectories with short time intervals during the execution of the mission is not feasible, hence an anytime approach using PSO is applied. This approach yields trajectories whose quality improves when available computation time increases. Thus, the method could be applied in realtime depending on the available computation time. The method has been validated with simulations in scenarios with multiple UAVs in a common workspace.

Reliability is a critical issue in navigation of unmanned aerial vehicles UAVs since there is no human pilot that can react to any abnormal situation. Due to size and cost limitations, redundant sensor schemes and aeronautical-grade navigation sensors used in large aircrafts cannot be installed in small UAVs. Therefore, other approaches like analytical redundancy should be used to detect faults in navigation sensors and increase reliability. This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters based on analytical redundancy. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the Observer/Kalman Filter Identification OKID method. The OKID method is able to identify the system and an observer with properties similar to a Kalman filter, directly from input-output experimental data. Results are similar to the Kalman filter, but, with the proposedmethod, there is no need to estimate neither system matrices nor sensor and process noise covariance matrices. The system has been tested with real helicopter flight data, and the results compared with other methods.

This paper presents a sensor fault detection and diagnosis system for small autonomous helicopters. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The observer is obtained from input-output experimental data with the observer/Kalman filter identification method. The system is tested with real helicopter flight data.

This paper presents a sensor fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The effectiveness of the proposed approach is demonstrated by means of MARVIN experimental results.

This paper presents a new approach that analyzes the stability of a general class of path tracking algorithms taking into account the pure delay in the control loop. The analysis has been done for straight paths and paths of constant curvature. This has sufficient generality since most usual paths can be decomposed in pieces of constant curvature. The method has been applied to the pure pursuit path tracking algorithm, one of the most widely used algorithms. The experiments performed with a computer controlled high mobility multi-purpose wheeled vehicle show good agreement with the theoretical predictions of the proposed method.

Path tracking is one of the most significant functions of autonomous vehicles and mobile robots. In general, tracking involves both sensing and control components.

This paper presents several control and perception components that implement navigation behaviours in autonomous vehicles. A behaviour-based control architecture integrating these components is also presented. The paper concentrates on autonomous tracking behaviours. In particular, the tracking of explicit paths, moving targets and environmental features are described. These behaviours have been implemented using several different position estimation techniques: dead reckoning; global position estimation using GPS; and position estimation with respect to the environment. The control architecture has been implemented in ROMEO vehicles at the University of Seville. These autonomous vehicles are adaptated from conventional electric vehicles and are currently used for experiments in autonomous navigation and teleoperation in outdoor environments. A short description of the general characteristics of the ROMEO-3R (tricycle) and ROMEO-4R (four wheels) vehicles is presented. The paper includes results from the tracking of environmenal features with proximity sensors, and visual tracking of moving targets.

The paper presents a multiple task-priorityinverse kinematics algorithm for a dual-arm aerial manipulator.Both tasks defined as equality constraints and inequalityconstraints are handled by means of a singularity robustmethod based on the Null-Space based Behavioral control.The proposed schema is constituted by the inverse kinematicscontrol, that receives the desired behavior of the system andoutputs the reference values for the motion variables, i.e.the UAV pose and the arm joints position, and a motioncontrol, that computes the vehicle thrusts and the jointtorques. The method has been experimentally validated ona system composed by an underactuated aerial hexarotorvehicle equipped with two lightweight 4-DOF manipulators,involved in operations requiring the coordination of the twoarms and the vehicle.

This paper presents the application of a multivariable frequency response technique to study the stability of autonomous vehicles when tracking a path. Particularly, the stability of a path tracking control loop with a fuzzy controller is considered. The technique is based on the analysis of the solutions of the harmonic balance equation. Necessary and sufficient conditions for stability areobtained by examining a family of characteristic loci parameterized in the amplitude. The method can be applied when pure delays exist in the path tracking control loop. Several simulations experiments have been done. These experiments show a Hopf bifurcation induced by a pure delay, and an unstable limit cycle around a stable origin.

Inspection and maintenance tasks are increasingly being carried out by multi-rotor platforms in order to avoid certain risks being taken by humans. In this way, it is necessary to have a good knowledge of the aerodynamic effects that occur when tasks are performed in confined environments. In addition, the use of tilted rotors is becoming more and more widespread for tasks that require direct contact with a surface. In that sense, this paper presents several numerical simulations to analyse the aerodynamic performance of tilted rotors. In particular, the wall effect and the corner effect will be shown in detail. Two different configurations are considered in the corner effect: straight and curved corner. The influence of the corner and the wall has been studied for three tilt angles $\left(\theta=\mathbf{2 0}^{\circ}, \mathbf{3 0}^{\circ}, \mathbf{4 0}^{\circ}\right)$ and various distances between the rotor and the wall. Flow field visualization is depicted to understand the physical behaviour of the airflow.

This paper presents the design, development and testing of a 4-DoF aerial manipulator for bridge inspection, where the arm is placed at the upper part of the multirotor body. The manipulator joints are equipped with a compliant mechanism that allows the contact with the environment reducing the influence over the platform stability. The transmission mechanism consists of two pairs of springs and a potentiometer for measuring the angular deflection between the servo and the joint angular position, which allows the estimation of the contact forces. Experimental tests have been done with the aerial manipulator placing the end effector at different points in the lower part of a bridge girder, which is needed by bridge inspectors to measure girder’s deflections over time.

This paper deals with steering and velocity control of outdoor autonomous vehicles. A fuzzy control system with two levels is used to track a path previously recorded or computed by means of a path planning program. In the first level a fuzzy logic system selects a goal point in the path to track taking into account the relative position and orientation of the vehicle, the curvature of the path ahead, and the vehicle's velocity. The second level generates the steering and velocity commands using the goal point provided by the first level and the current values of the vehicle's variables obtained by the sensors. The controller is computed by fuzzy identification using input and output data collected when a human is driving the vehicle. The determination of the number of fuzzy rules and the constant step-size is optimized to improve the convergence. The paper presents the application of the proposed method to the Romeo 3R outdoor mobile robot.