Path Planning and Real-Time Collision Avoidance Based on the Essential Visibility Graph

This paper deals with a novel procedure to generate optimum flight paths for multiple unmanned aircraft in the presence of obstacles and/or no-fly zones. A real-time collision avoidance algorithm solving the optimization problem as a minimum cost piecewise linear path search within the so-called Essential Visibility Graph (EVG) is first developed. Then, a re-planning procedure updating the EVG over a selected prediction time interval is proposed, accounting for the presence of multiple flying vehicles or movable obstacles. The use of Dubins curves allows obtaining smooth paths, compliant with flight mechanics constraints. In view of possible future applications in hybrid scenarios where both manned and unmanned aircraft share the airspace, visual flight rules compliant with International Civil Aviation Organization (ICAO) Annex II Right of Way were implemented. An extensive campaign of numerical simulations was carried out to test the effectiveness of the proposed technique by setting different operational scenarios of increasing complexity. Results show that the algorithm is always able to identify trajectories compliant with ICAO rules for avoiding collisions and assuring a 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

Distributed Reactive Model Predictive Control for Collision Avoidance of Unmanned Aerial Vehicles in Civil Airspace

Safety 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

Clothoid-Based Path Planning for a Formation of Fixed-Wing UAVs

Unmanned aerial vehicles (UAVs) are playing an increasingly crucial role in many appli cations such as search and rescue, delivery services, and military operations. However, one of the significant challenges in this area is to plan efficient and safe trajectories for UAV formations. This paper presents an optimization procedure for trajectory planning for fixed-wing UAV formations using graph theory and clothoid curves. The proposed planning strategy consists of two main steps. Firstly, the geometric optimization of paths is carried out using graphs for each UAV, providing piece-wise linear paths whose smooth connections are made with clothoids. Secondly, the geometric paths are transformed into time-dependent trajectories, optimizing the assigned aircraft speeds to avoid collisions by solving a mixed-integer optimal control problem for each UAV of the flight formation. The proposed method is effective in achieving suboptimal paths while ensuring collision avoidance between aircraft. A sensitivity analysis of the main parameters of the algorithm was conducted in ideal conditions, highlighting the possibility of decreasing the length of the optimal path by about 4.19%, increasing the number of points used in the discretization and showing a maximum path length reduction of about 10% compared with the average solution obtained with a similar algorithm using a graph based on random directions. Furthermore, the use of clothoids, whose parameters depend on the UAV performance constraints, provides smoother connections, giving a significant improvement over traditional straight-line or circular trajectories in terms of flight dynamics compliance and trajectory tracking capabilities. The method can be applied to various UAV formation scenarios, making it a versatile and practical tool for mission planning

HW VS SW sensor redundancy: Fault detection and isolation observer based approaches for inertial measurement units

In 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

Bi-level flight path optimization for UAV formations

A two-stage optimization model for flight path planning of cooperative UAVs in formation flight in the presence of polygonal obstacles and no-fly zones is proposed. Adopting a Visibility Graph (VG) approach, the virtual formation leader plans its flight path composed of circular arcs and segments connecting obstacles vertices. Then groups of obstacles, being not permeable by the flight formation without UAVs separation or formation shape deformation, are clustered and the VG is revised with the addition of so called rendez-vous waypoints, forcing the formation to be recomposed at a given location beyond groups of obstacles. Such rendez-vous waypoints are optimized at a higher hierarchical level with respect to the flight path optimization leading to a Stackelberg game. The validity of the proposed approach and optimization model is shown by means of numerical simulations where flight paths are obtained calculating shortest path on the revised Visibility Graph and waypoints positions are optimized via a genetic algorithm. Finally, anti-collision among UAVs is achieved via a simple potential based method

Re-entry trajectory tracking control of a micro-satellite system with a deployable front structure

This paper is focused on the design of a Model Predictive Control (MPC) algorithm for a micro-satellite with a mass of about 20 kg, equipped with an umbrella-like deployable front structure. This control device allows the vehicle to maneuver and track a prescribed trajectory during the re-entry phase by changing the aerobrake surface. The proposed MPC controller is aimed at minimizing the error between the desired target position at an altitude of about 30 km, after which the satellite follows an uncontrolled ballistic trajectory. A single control move is updated at a sampling rate of 0.1 Hz trying to balance performance with computational burden for a possible real time implementation. To prove that the proposed MPC strategy implies a limited loss of performance, a comparison with MPC controllers optimizing more than one control move has been carried out

Smooth Path planning for Fixed-Wing Aircraft in 3D Environment Using a Layered Essential Visibility Graph

This paper deals with the problem of flight path planning for unmanned fixed-wing air vehicles (UAVs) in complex 3D environments. Flight paths must be compliant with both mission constraints defined in terms of no-fly zones, obstacles and destination points and aircraft performance constraints such as maximum flight path angle and minimum turn radius.Trajectory generation is addressed as a minimum cost path search using a novel layered Essential Visibility Graph whose arcs and corresponding weights are obtained via an efficient branching algorithm to reduce computational time. The resulting path is a piecewise trajectory composed by only circular arcs and straight segments, according to Dubins paradigm. To prove the effectiveness of the proposed method, operational scenarios derived from real terrain morphology have been used

A Particle Filtering Approach for Fault Detection and Isolation of UAV IMU Sensors: Design, Implementation and Sensitivity Analysis

Sensor fault detection and isolation (SFDI) is a fundamental topic in unmanned aerial vehicle (UAV) development, where attitude estimation plays a key role in flight control systems and its accuracy is crucial for UAV reliability. In commercial drones with low maximum take-off weights, typical redundant architectures, based on triplex, can represent a strong limitation in UAV payload capabilities. This paper proposes an FDI algorithm for low-cost multi-rotor drones equipped with duplex sensor architecture. Here, attitude estimation involves two 9-DoF inertial measurement units (IMUs) including 3-axis accelerometers, gyroscopes and magnetometers. The SFDI algorithm is based on a particle filter approach to promptly detect and isolate IMU faulted sensors. The algorithm has been implemented on a low-cost embedded platform based on a Raspberry Pi board. Its effectiveness and robustness were proved through experimental tests involving realistic faults on a real tri-rotor aircraft. A sensitivity analysis was carried out on the main algorithm parameters in order to find a trade-off between performance, computational burden and reliability