1,721,013 research outputs found
Distributed Reactive Model Predictive Control for Collision Avoidance of Unmanned Aerial Vehicles in Civil Airspace
No full textSafety in the operations of UAVs (Unmanned Aerial Vehicles) depends on the current and future reduction of technical barriers and on the improvements related to their autonomous capabilities. Since the early stages, aviation has been based on pilots and Air Traffic Controllers that take decisions to make aircraft follow their routes while avoiding collisions. RPA (Remotely Piloted Aircraft) can still involve pilots as they are UAVs controlled from ground, but need the definition of common rules, of a dedicated Traffic Controller and exit strategies in the case of lack of communication between the Ground Control Station and the aircraft. On the other hand, completely autonomous aircraft are currently banned from civil airspace, but researchers and engineers are spending great effort in developing methodologies and technologies to increase the reliability of fully autonomous flight in view of a safe and efficient integration of UAVs in the civil airspace. This paper deals with the design of a collision avoidance system based on a Distributed Model Predictive Controller (DMPC) for trajectory tracking, where anticollision constraints are defined in accordance with the Right of Way rules, as prescribed by the International Civil Aviation Organization (ICAO) for human piloted flights. To reduce the computational burden, the DMPC is formulated as a Mixed Integer Quadratic Programming optimization problem. Simulation results are shown to prove the effectiveness of the approach, also in the presence of a densely populated airspace
Bi-level Flight Path Planning of UAV Formations with Collision Avoidance
No full textThis paper deals with the problem of generating 3D flight paths for a swarm of cooperating Unmanned Aerial Vechicles (UAVs) flying in a formation having a prespecified shape, in the presence of polygonal obstacles, no-fly zones and other non cooperative aircraft. UAVs are modeled as Dubins flying vehicles with bounds on the turning radius and flight path climb/descent angle. A Reduced Visibility Graph (RVG) based method, connecting selected nodes by means of circular arcs and segments, is adopted to minimize the length of each path. Then, to keep as much as possible the formation shape while flying between obstacles, the RVG is refined with the addition of so called Rendez-Vous Waypoints (RVWs). These are placed between groups of obstacles where it is impossible to maintain the desired formation. Waypoints locations and UAVs paths are optimized using a bi-level game theoretic approach based on the leader-follower Stackelberg model, where the lower level and upper level problems are the search of the shortest paths and the optimal locations of waypoints respectively. Such an approach allows to fly between obstacles, dispersing the formation and forcing UAVs to recompose it at given waypoints (RVWs) beyond groups of obstacles. Collision avoidance among UAVs and possible non-cooperative aircrafts, called intruders, is then achieved solving a set of linear quadratic optimization problems based on an original geometric based formulation. The effectiveness of the proposed approach is shown by means of numerical simulations where RVWs positions are optimized via a genetic algorithm
Fault tolerant low cost IMUS for UAVs
No full textIn this paper a Fault Tolerant system for the attitude estimation of an Unmanned Aerial Vehicle (UAV) using low cost magnetometers, accelerometers, and gyroscopes, implemented in an Inertial Measurement Unit (IMU) is proposed. An approach based on the Unscented Kalman Filter (UKF) for Detection, Isolation and Reconfiguration is investigated in the presence of a Hardware Duplex IMU mounted on board for flight control purposes. A state automaton, with comparative logics, detects if anomalies occurr on one of the two IMUs; then based on a comparison between the measured variables and their UKF estimations, the fault is isolated and identified. The proposed approach is an alternative to standard Hardware Triplex IMU architectures based on triple physical redundancy. At the expense of a higher computational cost and a small delay in isolating faults, the UKF based approach allows to limit the number of IMUs to two, or to guarantee a fail safe behavior in the presence of a double fault, even if contemporary, with Triplex IMUs. Experimental results on the implementation of a multiple IMU platform on a quadrotor flight control board are finally presented
A Cost-Effective Automatic Calibration Platform for Inertial Measurement Units
No full textIn the last decades, the growing use of small Unmanned Aerial Vehicles (UAVs) has resulted in an escalating demand for low-cost Inertial Measurement Units (IMUs), usually made of Micro Electro-Mechanical Systems (MEMS) to measure accelerations, angular velocities and, optionally, magnetic field components along three axes. An accurate calibration of these devices is needed for the precise determination of aircraft attitude. Although their versatile applications, MEMS-based IMUs exhibit a high level of noise, including both systematic and stochastic errors. Systematic errors need an appropriate calibration process to be identified and eliminated. This paper presents a portable low-cost IMU calibration platform to provide the parameters to mitigate the errors that characterize this kind of devices. Using three servomotors positioned to enable rotations around three orthogonal axes, the system allows for calibrating IMUs both statically and dynamically. To prove the effectiveness of the proposed platform, a performance evaluation is provided, showcasing the difference in estimating the attitude of an IMU, calibrated with and without the use of the platform
Distributed Collision Avoidance for Unmanned Aerial Vehicles Integration in the Civil Airspace
No full textThe Unmanned Aerial Vehicles (UAVs) integration in the civil air traffic will contribute to the reduction of technical barriers related to safety and operational challenges associated with enabling routine UAV access to the civil airspace. While manned aircraft involve pilots and the Air Traffic Controller to take decisions, and follow their preassigned paths to avoid collisions with other aircraft, UAVs still need the definition of algorithms and rules. In this paper, a collision avoidance algorithm based on International Civil Aviation Organization (ICAO) rules to resolve possible conflicts among aircraft that are on a collision course while flying to their respective destinations is proposed. The proposed algorithm is based on the combination of collision prediction, speed optimization and inverse proportional navigation algorithms. Different strategies are activated on the basis of the UAV status and in particular on the evaluation of the risk level leading the UAV in a de-confliction or avoidance mode. Numerical simulations are presented to show the effectiveness of the proposed approach in the presence of many UAVs
Path Planning and Risk Assessment in Unmanned Specific Operations
No full textUnmanned Aircraft Vehicles (UAV) have gained traction over the last two decades for diverse applications like sensing, surveillance, disaster response, and more. The absence of human pilots in UAVs offers advantages in risky scenarios. Ensuring safety is challenging, necessitating compliance with safety levels akin to manned aviation. Regulatory bodies are extending guidelines to cover drones. Specific Operations Risk Assessment (SORA) methodology, introduced by JARUS, aids risk assessment in UAV missions. This paper aims to develop a practical mission planning method adhering to safety rules, incorporating risk distribution across terrain. An optimization algorithm that balances fuel efficiency and risk reduction in trajectories is proposed, considering route efficiency alongside risk management
A Visibility Graph approach for path planning and real-time collision avoidance on maritime unmanned systems
No full textIn high navigation traffic areas, path planning and collision avoidance is a crucial element of safe navigation, mostly in view of possible future applications in hybrid scenarios where both manned and Autonomous Surface Vehicles (ASV) share the environment.This paper deals with a novel procedure to generate optimal paths in presence of static and moving obstacles. The proposed path planning approach deals with an optimization problem based on the so-called Essential Visibility Graph (EVG) [1], an extension of the standard Visibility Graph (VG) [2], in order to find the minimum cost piecewise linear path between two points in a scenario with several obstacles. Such approach can be used also in presence of multiple ASV or movable obstacles, by using a re-planning procedure to update the EVG over a selected prediction time interval. To make the solution compliant with the current regulation and make ASV behaviour predictable by human pilots on manned vehicles, EVG was extended by implementing a cut procedure based on Collision Regulations (COLREGS) [3]. Finally, the use of Dubins curves provides smooth paths, compliant with physics constraints such as the minimum turn radius.A campaign of numerical simulations was carried out to test the effectiveness of the proposed technique in different operational scenarios. Results show that the algorithm is always able to identify COLREGS-compliant trajectories, in order to avoid collisions and assure minimum safety distance as well. Furthermore, the low computational burden suggests that the proposed procedure can be considered a promising approach for real-time applications
Attitude and position estimation for an UAV swarm using consensus Kalman filtering
No full textThis paper presents the application of a distributed attitude and position estimation algorithm to a swarm of cooperating UAVs with heterogeneous sensors on board. The algorithm, based on a Consensus Extended Kalman Filtering (CEKF) to account for nonlinearities, is implemented assuming kinematic relationships. Numerical simulations are presented on different flight scenarios to evaluate the benefits of dealing with prior and novel information in a separate way on the basis of recent theoretical results on CEKF. Inertial and vision sensors are supposed to be mounted on board of the aircraft. Realistic flight scenarios are analyzed in the light of possible time communication delays among the agents
A Consensus-Based Kalman Filter for Target Localization in Emergency Scenarios
No full textIn the last years, Unmanned Aerial Vehicles (UAVs) have been widely used for several types of missions, including aerial reconnaissance, search and rescue, and military operations. In first rescue missions, the ability to detect missing people after avalanche events in a short time is fundamental to increase the probability of saving them. The use of unmanned aerial vehicles in such scenarios can improve results with respect to multiple points of view: on the one hand, it can decrease the danger for rescuers, while on the other hand, it can speed up the search process. An effective solution can be the involvement of a formation of multiple drones to cover a greater research space and accelerate the process. However, an important challenge in deploying a formation of robots in emergency scenarios is the autonomy in terms of system scalability, since drones are usually teleoperated in a one-to-one ratio with operators, requiring a large crew of rescuers. In order to improve the situational awareness and distribute the communication burden, this paper deals with a decentralized Kalman filtering algorithm using sensor data from multiple drones to estimate a target position, besides UAVs state to support guidance and control algorithms. Such decentralized Kalman filtering algorithm combines the characteristics of Consensus on Information and Consensus on Measurement techniques. The proposed technique is preliminarily validated by means of numerical simulations on an example scenario
HW VS SW sensor redundancy: Fault detection and isolation observer based approaches for inertial measurement units
No full textIn this paper the use of different observer schemes based on Kalman Filtering for the detection and isolation of aircraft abrupt and incipient sensor faults on Inertial Measurement Units (IMUs) is discussed. The possibility of using a dynamic 6DoF model of the aircraft is explored and compared with the use of a purely kinematic model. Both the possibilities are investigated assuming that two IMUs are available on board, and the analytic redundancy provided by the observers is used to vote the healthy one, when a fault occurs on accelerometers, gyros or magnetometers. The proposed schemes are applied to simulated flight data of a General Aviation aircraft generated in the presence of disturbances and uncertainties. Preliminary experimental results using two low cost IMUs are also shown for possible applications to improve safety and reliability of small Unmanned Air Vehicles
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