Top PDF Auto-Landing System for Fixed-Wing Unmanned Aerial Vehicle

Auto-Landing System for Fixed-Wing Unmanned Aerial Vehicle

Auto-Landing System for Fixed-Wing Unmanned Aerial Vehicle

Amit and Padhi [2] researched autonomous landing using tracking-model predictive static programming guidance and dynamic inversion auto-pilot. Their approach was similar to this thesis as it followed a desired trajectory landing path. There were, however, a few differences between the two approaches. While the approach of this thesis was to use experimental data to compute the transfer function of the plane, Amit and Padhi used a state space theoretical model with six degrees of freedom. Another difference was the number of control loops employed in the respective models. Amit and Padhi used an outer and inner control loop, with the outer loop optimized for the control of the deviation across the landing trajectory and the inner loop tuned for the implementation of the dynamic inversion technique, control of body rates, and forward velocity. Lastly the treatment of the landing phases differed as they sectioned the landing into phase circular orbit, glideslope, and flare. This paper was largely theoretical but mathematically comprehensive. The goals of both papers were similar, though the approach was rather different.
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Lift System Design of Tail Sitter Unmanned Aerial Vehicle

Lift System Design of Tail Sitter Unmanned Aerial Vehicle

Quadrotor helicopter is a kind of vertical take-off and landing (VTOL) multi-rotor unmanned aerial vehicles (UAV). This kind of helicopter has many characteristics e.g., stable hovering and maneuverable flight in tough environment, its important advantage is load capacity. As these advantages, quadrotor helicopter has many utilities, such as search and rescue, building exploration, security and inspection, etc. especially in dangerous and inacces- sible environments. So the aircraft has been widely used in various fields due to the advantages, such as air trans- port, crop monitoring and military reconnaissance. Con- ventional fixed-wing aircraft can fly at very high flight speed, but must rely on the runway in taking off and landing process. On the contrary, the helicopter can take off vertically out of the shackles of the runway, but its flight speed has been greatly hindered. After the Second World War, some companies in the United States, Can- ada and Europe started to develop a kind of vertical take- off and landing (VTOL) aircraft which has the advan- tages of both fixed-wing aircraft and helicopter, obtain- ing high speed at the same time getting rid of the de- pendence on the runway.
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Capabilities of low cost and fast image acquisition using micro fixed-wing unmanned aerial vehicle system

Capabilities of low cost and fast image acquisition using micro fixed-wing unmanned aerial vehicle system

However, there are some limitations or draw back for these methods. The problem related to this technology is the difficulties of possessing clear image of the study area. According to [5], the limitation of satellites and manned aircraft are flight costs, slow and weather-dependent data collection, limited availability, limited flying time, low ground resolution. In aerial photogrammetry, the aircraft can be flown under the cloud and imagery can be obtained much easier than satellite imagery.

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Assessment of photogrammetric micro fixed-wing unmanned aerial vehicle (UAV) system for image acquisition of coastal area

Assessment of photogrammetric micro fixed-wing unmanned aerial vehicle (UAV) system for image acquisition of coastal area

Fast image acquisition is the most important part for societal impact of a developing country. This paper aims to demonstrate the potential use of micro fixed wing unmanned aerial vehicle (UAV) system attached with high resolution digital camera for coastal mapping. In this study, six strips of aerial images of coastal area was captured using a high resolution compact digital camera known as Canon Power Shot SX230 HS and it has 12 megapixel image resolution. From the aerial images, photogrammetric image processing method is completed to produce mapping outputs such a digital elevation model (DEM) and orthophoto. For accuracy assessment, the coordinates of the selected points in the 3D of stereomodel were compared to the conjugate points observed using GPS and the root mean square error (RMSE) is computed. From this study, the results showed that the achievable RMSE are ± 0.018m, ± 0.013m and ± 0.034m for coordinates X, Y and Z respectively. It will anticipate that the UAV will be used for coastal survey and improve current method of producing with low cost, fast and good accuracy. Finally, the UAV has shown great potential to be used for coastal mapping that require accurate results or products using high resolution camera.
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Automated landing of a quadrotor Unmanned Aerial Vehicle on a translating platform

Automated landing of a quadrotor Unmanned Aerial Vehicle on a translating platform

Attention is now shifted towards other aerodynamic effects that play a role while landing a rotorcraft. An aerodynamic effect that is relevant to automated landings is the IGE. According to Schmaus et al., IGE is a term used to describe the changes in performance that rotorcraft and fixed-wing aircraft experience as they approach the ground [23]. Schmaus et al. further state that the IGE is often viewed as an increase in thrust for a constant power, which can be beneficial in some applications, but not for an automated landing where the aircraft dynamics are changing. When a rotorcraft is subject to IGE conditions, the wake of a helicopter rotor interacts with the ground and causes significant perturbation to the flow near the rotor blades, as well as the rest of the craft [24]. IGE therefore effectively disturbs the aircraft, which is not favorable while the aircraft is translating near the platform. The IGE, to its full extent, is not applicable to this project. The platform which is avail- able in the ESL, and which the aircraft will be landing on, is perforated. The perforated surface allows the wake from the rotors to partially pass through the platform. The effect from coming close to the platform is therefore decreased, but not completely absent. As a consequence, it might be worthwhile to investigate this phenomena separately.
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Unmanned Aerial Vehicle (UAV) Monitoring Surveillance System

Unmanned Aerial Vehicle (UAV) Monitoring Surveillance System

Among the first three categories above, there is a Vertical Take-Off and Landing (VTOL) type of UAVs. This aerial type platform has the ability to take off and land vertically, as well as to hover around the ground, but lacks in range capability [6]. Also, a new category of UAV has been emerged which is the Micro Air Vehicles. It‟s being categorized by its tiny size of no more than 15 cm wing wide span and length [1].

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A neural network based landing method for an unmanned aerial vehicle with soft landing gears

A neural network based landing method for an unmanned aerial vehicle with soft landing gears

Flying animals, such as birds, can perch on trees, poles, and other non-flat surfaces which are not suitable for UAV landing. Equipped with this soft landing ability, birds may occupy a high vantage point [10]. They can stay there to search, forage, and rest for an extended period of time [11,12]. As a high-challenge landing approach, perching refers to precise landing pose control and the effectiveness of energy absorption [13]. Cory and Tedrake, of the MIT Computer Science and Artificial Intelligence Laboratory, have analyzed and presented fixed-wing precise drone landing tests and demonstrated that angles of attack are critical factors during the touchdown procedure [14]. Mirko Kovac from the Imperial College of London designed an aerial robot equipped with soft shock absorbers which can land on a convex surface with diameter longer than robot’s body length [15]. Subsequently, many inspired mechanical devices have been investigated to test this hypothesis. For example, a pitch-up touchdown sequence, consisting of distance detection, UAV nose up, and soft
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Disturbance rejection flight control for small fixed-wing unmanned aerial vehicles

Disturbance rejection flight control for small fixed-wing unmanned aerial vehicles

performance in the presence of wind disturbances. This control scheme uses nonliner dynamics inversion to address the nonlinearities in the flight dynamics so that it can follow the reference commands in airspeed and height. A novel nonlinear disturbance observer is designed based on the nominal aircraft model to provide estimates of the wind influences and system uncertainties. These estimates are then used to form the compensation control efforts. The developed scheme has been tested in the simulation studies, with scenarios of landing profile tracking and straight flight under wind disturbances and parameter uncertainties. The results have shown a significant improvement in control accuracy and robustness comparing to the baseline controllers and the controller with in- tegral actions. It should be noted that although the current disturbance observer solution is tailored to the particular problem described in this note, this method may be of interest in many similar flight control applications for different aircraft.
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Autonomous landing of a fixed-Wing unmanned aircraft with partialwing and stabiliser losses

Autonomous landing of a fixed-Wing unmanned aircraft with partialwing and stabiliser losses

Unmanned aerial vehicles (UAVs) are becoming more popular for military as well as commercial use. Removing the human aspect from the machine results in a system that can operate in more harsh environments and for longer periods. A few examples of the ever-expanding applications of UAVs are notably combat missions, search and rescue, disaster management, surveying and also as delivery systems. A UAV is typically adapted for a specific application, which allows it to perform at its best for the given mission. Each application introduces new uncertainties and complications that need to be considered in the development process. A fully autonomous UAV is capable of performing autonomous take-off, navigation and landings, which all form part of the typical aircraft phases or tasks seen in Figure 1.1. Of all these tasks, landing the aircraft is the most difficult. Landing typically entails aligning the aircraft with the runway, reducing the aircraft’s airspeed (which is kept well above stall speed) and following a glide path at a certain sink rate until touchdown. For a UAV to successfully perform a fully autonomous landing, strict longitudi- nal and lateral-directional control are required to ensure that the aircraft follows the desired glide path and stays within the runway bounds while approaching the touchdown point. A significant amount of research continues to go into the development of UAVs and how they can reliably in- tegrated into military and civil airspace. Human safety is one of the most important factors that needs to be considered before sending a UAV into missions.
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Autonomous Vertical Recovery  of Fixed Wing Unmanned Aerial Vehicles

Autonomous Vertical Recovery of Fixed Wing Unmanned Aerial Vehicles

Autonomous fixed-wing UAV recovery, the subject of this thesis, is predicated on electric propulsion to maintain controlled orientation and descent of the aircraft. The controlled descent of such an aerodynamic body diverges significantly from standard multi-rotor control by the necessity to conduct these manoeuvres far outside the intended operational envelope of the airframe. The control effort required to successfully complete an autonomous descent and landing can be studied in two parts. First would be the control of the orientation of the aircraft and second, the control of the aircraft translation in space relative to an inertial frame. For standard multi-rotor or helicopter control, orientation is used to directly control translational motion since the thrust vector is approximately fixed to the vertical axis of the aircraft’s body frame. For vertical descent fixed-wing UAV recovery this topology leads to control difficulties related to disturbances generated by the aircraft’s lift generating surfaces. The autonomous landing manoeuver requires that the aircraft counteract wind speed during the descent so that at the moment of touchdown there is zero ground speed. The natural consequence of this requirement is motion in the wind frame that acts on the lift generating surfaces of the UAV according to the angle of attack (α) and sideslip angle (β). Analyses of these forces which are beyond the scope of this thesis will be generally considered as disturbances affecting the system as shown in Figure 10.
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Fault-tolerant flight control for a fixed-wing unmanned aerial vehicle with partial horizontal and vertical stabiliser losses

Fault-tolerant flight control for a fixed-wing unmanned aerial vehicle with partial horizontal and vertical stabiliser losses

The closed-loop poles of the system were investigated to determine the robustness of the flight control system. Figure 5.28 shows a cloud of the closed-loop poles of the aircraft with all the longitudinal and lateral controllers added in. This agrees with Section 5.2.2 regarding the changes in the closed-loop poles due to the partial stabiliser loss. This also shows that as the horizontal and vertical stabiliser were partially removed, the closed-loop poles of the controllers of the system were still in the left-hand plane of the pole plot indicating that they were stable after the induced damage. The larger damage cases showed the plant poles nearing the right- hand plane and approaching instability. In these borderline cases, the aircraft might actually not have been stable due to the actuator limitations. Some of the inner-loop controllers on the damaged aircraft configurations had noticeable differences in their responses and pole locations when compared to the healthy one. However, the outer-loop controllers remained consistent in their response from the healthy to damaged configuration. This indicates that the control system is capable of controlling the nominal aircraft damage configuration.
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Event-Based Visual-Inertial Odometry on a Fixed-Wing Unmanned Aerial Vehicle

Event-Based Visual-Inertial Odometry on a Fixed-Wing Unmanned Aerial Vehicle

they released the Event Camera Dataset [3]. The calibration parameters are provided as a text file with (f x , f y , c x , c y , k 1 , k 2 , p 1 , p 2 , k 3 ) which provides the camera matrix parameters and distortion coefficients explained in Section 2.1.1. The DAVIS output is available either as text files for events, IMU measurements, and image timestamps with a folder of ”.png” images or as a rosbag binary file compatible with Robot Operating System (ROS), a multi-purpose robotic software framework. The company iniVation has also provided a toolbox on GitHub [148] for MATLAB that can convert rosbag binary files to an custom ”address-event data” (.aedat) binary file with tools to easily accomplish various tasks, including loading custom selections of the data into a MATLAB struct, reorienting the images or event data, normalizing timestamps off the first timestamp, and various visualizing/plotting methods.
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Design and Optimization of Wing Structure for a Fixed Wing Unmanned Aerial Vehicle (UAV)

Design and Optimization of Wing Structure for a Fixed Wing Unmanned Aerial Vehicle (UAV)

DOI: 10.4236/mme.2018.84017 255 Modern Mechanical Engineering and effective height ratio are considered purely from the structural point of view. In fact, the choice of structural load types is largely influenced by many factors in the overall layout of aircraft and needs comprehensive measurement. The first aspect is about internal layout of wing, such as retractable landing gear, large openings, etc. The second aspect is the relative position of the wing and the fu- selage, as well as the interior of the fuselage. The third aspect is the geometric parameters of the wing, such as swept wing, delta wing, etc.
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Autonomous landing of a fixed-wing unmanned aerial vehicle onto a moving platform

Autonomous landing of a fixed-wing unmanned aerial vehicle onto a moving platform

Figure 7.48: NSA spike for a moving platform landing and recovery during HIL simulations. was simply commanded to track the trim altitude after the touchdown was detected, while the roll angle was commanded to remain wings-level. It was decided to not command a high pitch angle to quickly increase angle of attack and therefore gain additional lift during this procedure. The resulting large pitch rate may cause the tail to strike the platform, thereby damaging the undercarriage, elevator or the servo motors. Figure 7.50 shows the large deviation in airspeed during the touch-and-go manoeuvre. The reason for this is twofold. Firstly, the aircraft experiences a large backwards force due to dynamic friction when the wheels come into contact with the platform surface, especially since the wheels are prone to bending under large downwards forces. Secondly, the large altitude step also causes the controllers to exchange some kinetic energy for potential energy, thus lowering the airspeed. The specific energy integrator may not wind down fast enough after the altitude is reached, therefore causing the overshoot in airspeed. The manoeuvre is however performed successfully and deemed acceptable for practical flight.
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Autonomous landing of a fixed-wing unmanned aerial vehicle using differential GPS

Autonomous landing of a fixed-wing unmanned aerial vehicle using differential GPS

This thesis has presented the design and practical demonstration of a flight control system that is capable of autonomously landing a fixed-wing UAV on a stationary platform, aided by a high- precision GPS. The project forms part of on-going research in ATOL at Stellenbosch University with the end goal of landing a fixed-wing UAV on a moving platform, for example on a ship’s deck. The selected airframe was equipped with the standard ESL avionics stack. The airframe’s aerodynamic coefficients were determined via AVL and the equipped aircraft’s mass moment of inertia was obtained by the double pendulum method. The stall speed of the airframe was also determined in AVL and practically flight tested. With a flight-ready aircraft, the scene was set for controller design and testing. The inner-loop and outer-loop controllers were designed based on the acceleration-based manoeuvre autopilot architecture [1]. In preparation for a practical flight test, the designed flight controllers were tested in SIL and HIL simulations to verify the performance of the FCS and to minimise risk. With an equipped airframe and practically flight-tested controllers, the scene was also set to test the developed landing state machine via virtual deck landings tests. Then with enough confidence gained in the FCS and to enable the FCS to perform practical landings, Novatel’s high-precision GPS was integrated into the aircraft and the FCS OBC code. Considerable time went into testing the FCS with the new DGPS to ensure the desired operation. Landing simulations were repeated in SIL and HIL simulation to test the FCS robustness and execution of the landing state machine to minimise risk before practical landing tests.
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Autonomous take-off and landing of a fixed wing unmanned aerial vehicle

Autonomous take-off and landing of a fixed wing unmanned aerial vehicle

The tests will range from hardware (sensor) testing to controller testing for full autonomous flight and runway ground speed and yaw rate control. The hardware test will [r]

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Cooperative Control for Landing a Fixed-Wing Unmanned Aerial Vehicle on a Ground Vehicle

Cooperative Control for Landing a Fixed-Wing Unmanned Aerial Vehicle on a Ground Vehicle

Descent using switching descent law Since it was evident that using a normal decent law would not be robust enough, testing turned towards using a switching strategy. The biggest drawback of such a method is that unexpected behavior might occur when going between different flight modes. Guaranteeing that a switching controller will perform a certain way can be difficult because of the hybrid nature of the total system. It is known that even a combination of stable subsystems might become unstable when used together with a switching control if used incorrectly [23]. Another reason why it might be difficult to design such a system is that it is difficult to foresee what might happen with different combinations of system states and control modes. An example of this type of problematic behavior can be seen in Figure 8.4, where the retry mode and the coupling in velocity and altitude causes the x position to oscillate as the altitude is going between h 1 = 10 m and h 0 = 5 m. The change in x causes further retries,
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A smart Neural Network Based Algorithm for Landing Control of Autonomous Unmanned Aerial Vehicle

A smart Neural Network Based Algorithm for Landing Control of Autonomous Unmanned Aerial Vehicle

1177 | P a g e included a method referred as deep stall landing, the advantage of the proposed method is that it can be used in landing in small space, where the UAV is in a deep stall when the angle of attack is greater than the stall angle, which cause UAV to lose height fast, an accurate control algorithm is a preliminary requirement for such method, delta wing UAV was used. while the another in work [6], has used the same optimal control; continuous model predictive control (MPC) method for landing control of UAV, the algorithm assumes the controlled plant as a multi-input system (an optimal constraint problem), in aspect of speed and descent rate which are basic concern during the landing final approach phase, a mathematical module of UAV was has been derived and an optimal problem was formulated and simulated the obtained results was compared with results obtained from simulating the same model with PID controller, and the MPC has given the best results, the approach is quite useful for autonomous landing but neglected the first phase of the landing .
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Unmanned Aerial Surveillance Vehicle

Unmanned Aerial Surveillance Vehicle

Lastly after constructing the drone we will perform trials using a camera on board and then validate the structural stability of the drone using simulation software (ANSYS). India’s present development of Unmanned Aerial Vehicle (UAVs) and Smaller Drones locally is pathetically low to meet a large number of requirements felt by the Indian Armed forces, with technology trajectory of UAV’s and Drones moving to next level in the usage of their military applications.

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Quadrotor – An Unmanned Aerial Vehicle

Quadrotor – An Unmanned Aerial Vehicle

In nowadays the development of small UAV is under the interest of many researchers and want to explore the application. There is currently a large range of projects and research topics emerging in this field. Preliminary research has shown that the most versatile and mechanically easy to construct UAV is a quadrotor helicopter. This is due to the fact that quadrotor aerial robot is an automatic system which is an unmanned VTOL (vertical take-off and landing) helicopter. Quadrotors can be controlled by varying the speed of the four rotors and no mechanical linkages are required to vary the rotor blade pitch angles as compare to a conventional helicopter.
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