Unmanned aerial vehicles (UAVs) are mainly used by military and government organizations, but with low-cost sensors, electronics, and airframes there is significant interest in using low-cost UAVs among aircraft hobbyists, academic researchers, and industries. Applications such as mapping, search and rescue, patrol, and surveillance require the UAV to autonomously follow a predefined path at a prescribed height. The most commonly used paths are straight lines and circular orbits. Path-following algorithms ensure that the UAV will follow a predefined path in three or two dimensions at constant height. A basic requirement for these path-following algorithms is that they must be accurate and robust to wind disturbances.

Unmanned Aerial Vehicle Path Following: A Survey and Analysis of Algorithms for Fixed-Wing Unmanned Aerial Vehicless

This paper addresses two interrelated problems concerning the planar three degree-of-freedom motion of a vehicle, namely, the path planning problem and the guidance problem. The monotone cubic Hermite spline interpolation (CHSI) technique by Fritsch and Carlson is employed to design paths that provide the user with better shape control and avoid wiggles and zigzags between the two successive waypoints. The conventional line-of-sight (LOS) guidance law is modified by proposing a time-varying equation for the lookahead distance, which is a function of the cross-track error. This results in a more flexible maneuvering behavior that can contribute to reaching the desired path faster as well as obtaining a diminished oscillatory behavior around the desired path. The guidance system along with a heading controller form a cascaded structure, which is shown to be $\kappa$ -exponentially stable when the control task is to converge to the path produced by the aforementioned CHSI method. In addition, the issue of compensating for the sideslip angle $\beta$ is discussed and a new $\kappa$ -exponentially stable integral LOS guidance law, capable of eliminating the effect of constant external disturbances for straight-line path following, is derived.

Integral LOS Path Following for Curved Paths Based on a Monotone Cubic Hermite Spline Parametrization

Military unmanned aerial vehicles (UAVs) are employed in highly dynamic environments and must often adjust their trajectories based on the evolving situation. To operate autonomously and safely, a UAV must be equipped with a path planning module capable of quickly recalculating a feasible and quasi-optimal path in flight while in the event a new obstacle or threat has been detected or simply if the destination point is changed during the mission. To allow for a fast path planning, this paper proposes a parallel implementation of the genetic algorithm on graphics processing unit (GPU). The trajectories are built as series of line segments connected by circular arcs resulting in smooth paths suitable for fixed-wing UAVs. The fitness function we defined takes into account the dynamic constraints of the UAVs and aims to minimize fuel consumption and average flying altitude in order to improve range and avoid detection by enemy radars. This fitness function is also implemented on the GPU and different parallelization strategies were developed and tested for each step of the fitness evaluation. By exploiting the massively parallel architecture of GPUs, the execution time of the proposed path planner was reduced by a factor of 290x compared to a sequential execution on CPU. The path planning module developed was tested using 18 scenarios on six realistic three-dimensional terrains with multiple no-fly zones. We found that the proposed GPU-based path planner was able to find quasi-optimal solutions in a timely fashion allowing in-flight planning.

Fast Genetic Algorithm Path Planner for Fixed-Wing Military UAV Using GPU

The control of equipment such as camera gimbal, Vertical Take-Off and Landing (VTOL) and Load Transporting System (LTS) on Unmanned Aerial Vehicle (UAV) with its own flight control directly affects the performance of the mission in tasks such as tracking the target along the specified path and leaving payloads on the targets specified in the dangerous areas. In this study, neural network based real-time control of a hexarotor UAV is performed so that the payloads on the targets determined by path tracking can be left with minimum error. The Nonlinear AutoRegressive eXogenous (NARX) model of the UAV is obtained after the flight data are passed through the pre-processing, feature extraction and feature selection stages. The obtained neural network model is embedded in the flight control card to realize real time path tracking of the UAV. The three payloads in the cubic structure are both transported by the originally designed LTS and left with the help of LTS to targets on the path. Environmental testing is conducted taking into account the limitations of the physical properties of the LTS and specified path tracking on the autonomously moving UAV, and the impact on proposed NARX control algorithm’s mission performance is examined.

Real-Time Control based on NARX Neural Network of Hexarotor UAV with Load Transporting System for Path Tracking

This paper presents a feasible 3D collision avoidance approach for fixed-wing unmanned aerial vehicles (UAVs) The proposed strategy aims to achieve the desired relative bearing in the horizontal plane and relative elevation in the vertical plane so that the host aircraft is able to avoid collision with the intruder aircraft in 3D The host aircraft will follow a desired trajectory in the collision avoidance course and resume the pre-arranged trajectory after collision is avoided The approaching stopping condition is determined for the host aircraft to trigger an evasion maneuver to avoid collision in terms of measured heading A switching controller is designed to achieve the spatial collision avoidance strategy Simulation results demonstrate that the proposed approach can effectively avoid spatial collision, making it suitable for integration into flight control systems of UAVs

/pdf/a-3d-collision-avoidance-strategy-for-uavs-in-a-non-2r2555dhft.pdf

A 3D Collision Avoidance Strategy for UAVs in a Non-Cooperative Environment

In this brief, we consider the problem of 3-D path generation and tracking for unmanned air vehicles (UAVs). The proposed path generation algorithm allows us to find a path satisfying arbitrary initial and final conditions, specified in terms of position and velocity. Our method assumes that aircraft structural and dynamic limitations can be translated in a turn radius constraint; therefore, the generated paths satisfy a constraint on the minimum admissible turning radius. The proposed algorithm for the path tracking guarantees, under specified assumptions, that the tracking error, both in position and in attitude, asymptotically tends to zero. The work has been carried out with reference to the UAV of the Italian Aerospace Research Center (CIRA). Simulation results for both the path generation and the tracking algorithms are presented; the latter have been obtained using a detailed 6-degree-of-freedom model of the CIRA UAV in the presence of wind and turbulence.

E. De Lellis

Papers

Path Generation and Tracking in 3-D for UAVs