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In the last decade, signi?cant changes have occurred in the ?eld of vehicle motion planning, and for UAVs in particular. UAV motion planning is especially dif?cult due to several complexities not considered by earlier planning strategies: the - creased importance of differential constraints, atmospheric turbulence which makes it impossible to follow a pre-computed plan precisely, uncertainty in the vehicle state, and limited knowledge about the environment due to limited sensor capabilities. These differences have motivated the increased use of feedback and other control engineering techniques for motion planning. The lack of exact algorithms for these problems and dif?culty inherent in characterizing approximation algorithms makes it impractical to determine algorithm time complexity, completeness, and even soundness. This gap has not yet been addressed by statistical characterization of experimental performance of algorithms and benchmarking. Because of this overall lack of knowledge, it is dif?cult to design a guidance system, let alone choose the algorithm. Throughout this paper we keep in mind some of the general characteristics and requirements pertaining to UAVs. A UAV is typically modeled as having velocity and acceleration constraints (and potentially the higher-order differential constraints associated with the equations of motion), and the objective is to guide the vehicle towards a goal through an obstacle ?eld. A UAV guidance problem is typically characterized by a three-dimensional problem space, limited information about the environment, on-board sensors with limited range, speed and acceleration constraints, and uncertainty in vehicle state and sensor data.

Inhaltsverzeichnis

Frontmatter

Editorial

From the Editor-in-Chief
I wish you a Happy New Year, full of health, happiness, prosperity, success, and may all your wishes become reality.
Kimon P. Valavanis

Accurate Modeling and Robust Hovering Control for a Quad-rotor VTOL Aircraft

Quad-robot type (QRT) unmanned aerial vehicles (UAVs) have been developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV is equipped with four propellers driven by each electricmotor, an embedded controller, an Inertial Navigation System (INS) using three rate gyros and accelerometers, a CCD (Charge Coupled Device) camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. Accurate modeling and robust flight control of QRT UAVs are mainly discussed in this work. Rigorous dynamic model of a QRT UAV is obtained both in the reference and body frame coordinate systems. A disturbance observer (DOB) based controller using the derived dynamic models is also proposed for robust hovering control. The control input induced by DOB is helpful to use simple equations of motion satisfying accurately derived dynamics. The developed hovering robot shows stable flying performances under the adoption of DOB and the vision based localization method. Although a model is incorrect, DOB method can design a controller by regarding the inaccurate part of the model and sensor noises as disturbances. The UAV can also avoid obstacles using eight IR (Infrared) and four ultrasonic range sensors. This kind of micro UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment. The experimental results show the performance of the proposed control algorithm.
Jinhyun Kim, Min-Sung Kang, Sangdeok Park

Modeling and System Identification of the muFly Micro Helicopter

An accurate mathematical model is indispensable for simulation and control of a micro helicopter. The nonlinear model in this work is based on the rigid body motion where all external forces and moments as well as the dynamics of the different hardware elements are discussed and derived in detail. The important model parameters are estimated, measured or identified in an identification process. While most parameters are identified from test bench measurements, the remaining ones are identified on subsystems using the linear prediction error method on real flight data. The good results allow to use the systems for the attitude and altitude controller design.
Dario Schafroth, Christian Bermes, Samir Bouabdallah, Roland Siegwart

Vision-based Position Control of a Two-rotor VTOL miniUAV

In this paper we address the stabilization of the attitude and position of a birotor miniUAV to perform autonomous flight. For this purpose, we have implemented a Kalman-based sensor fusion between inertial sensors (gyros-accelerometers) and the optical flow (OF) provided by the vehicle. This fusion algorithm extracts the translational-OF (TOF) component and discriminates the rotational OF (ROF). The aircraft’s position is obtained through an object detection algorithm (centroid tracking). Newton-Euler motion equations were used to deduce the mathematical model of the vehicle. In terms of control we have employed a saturated-based control to stabilize the state of the aircraft around the origin. Experimental autonomous flight was successfully achieved, which validates the sensing strategy as well as the embedded control law.
E. Rondon, S. Salazar, J. Escareno, R. Lozano

A Survey of Motion Planning Algorithms from the Perspective of Autonomous UAV Guidance

A fundamental aspect of autonomous vehicle guidance is planning trajectories. Historically, two fields have contributed to trajectory or motion planning methods: robotics and dynamics and control. The former typically have a stronger focus on computational issues and real-time robot control, while the latter emphasize the dynamic behavior and more specific aspects of trajectory performance. Guidance for Unmanned Aerial Vehicles (UAVs), including fixed- and rotary-wing aircraft, involves significant differences from most traditionally defined mobile and manipulator robots. Qualities characteristic to UAVs include non-trivial dynamics, three-dimensional environments, disturbed operating conditions, and high levels of uncertainty in state knowledge. Otherwise, UAV guidance shares qualities with typical robotic motion planning problems, including partial knowledge of the environment and tasks that can range from basic goal interception, which can be precisely specified, to more general tasks like surveillance and reconnaissance, which are harder to specify. These basic planning problems involve continual interaction with the environment. The purpose of this paper is to provide an overview of existing motion planning algorithms while adding perspectives and practical examples from UAV guidance approaches.
C. Goerzen, Z. Kong, B. Mettler

An Efficient Path Planning and Control Algorithm for RUAV’s in Unknown and Cluttered Environments

This paper presents an efficient planning and execution algorithm for the navigation of an autonomous rotary wing UAV (RUAV) manoeuvering in an unknown and cluttered environment. A Rapidly-exploring Random Tree (RRT) variant is used for the generation of a collision free path and linear Model Predictive Control(MPC) is applied to follow this path. The guidance errors are mapped to the states of the linear MPC structure by using the nonlinear kinematic equations. The proposed path planning algorithm considers the run time of the planning stage explicitly and generates a continuous curvature path whenever replanning occurs. Simulation results show that the RUAV with the proposed methodology successfully achieves autonomous navigation regardless of its lack of prior information about the environment.
Kwangjin Yang, Seng Keat Gan, Salah Sukkarieh

On the Generation of Trajectories for Multiple UAVs in Environments with Obstacles

This paper presents a methodology based on a variation of the Rapidly-exploring Random Trees (RRTs) that generates feasible trajectories for a team of autonomous aerial vehicles with holonomic constraints in environments with obstacles. Our approach uses Pythagorean Hodograph (PH) curves to connect vertices of the tree, which makes it possible to generate paths for which the main kinematic constraints of the vehicle are not violated. These paths are converted into trajectories based on feasible speed profiles of the robot. The smoothness of the acceleration profile of the vehicle is indirectly guaranteed between two vertices of the RRT tree. The proposed algorithm provides fast convergence to the final trajectory. We still utilize the properties of the RRT to avoid collisions with static, environment bound obstacles and dynamic obstacles, such as other vehicles in the multi-vehicle planning scenario. We show results for a set of small unmanned aerial vehicles in environments with different configurations.
Armando Alves Neto, Douglas G. Macharet, Mario F. M. Campos

Integration of Path/Maneuver Planning in Complex Environments for Agile Maneuvering UCAVs

In this work, we consider the problem of generating agile maneuver profiles for Unmanned Combat Aerial Vehicles in 3D Complex environments. This problem is complicated by the fact that, generation of the dynamically and geometrically feasible flight trajectories for agile maneuver profiles requires search of nonlinear state space of the aircraft dynamics. This work suggests a two layer feasible trajectory/maneuver generation system. Integrated Path planning (considers geometrical, velocity and acceleration constraints) and maneuver generation (considers saturation envelope and attitude continuity constraints) system enables each layer to solve its own reduced order dimensional feasibility problem, thus simplifies the problem and improves the real time implement ability. In Trajectory Planning layer, to solve the time depended path planning problem of an unmanned combat aerial vehicles, we suggest a two step planner. In the first step, the planner explores the environment through a randomized reachability tree search using an approximate line segment model. The resulting connecting path is converted into flight way points through a line-of-sight segmentation. In the second step, every consecutive way points are connected with B-Spline curves and these curves are repaired probabilistically to obtain a geometrically and dynamically feasible path. This generated feasible path is turned in to time depended trajectory with using time scale factor considering the velocity and acceleration limits of the aircraft. Maneuver planning layer is constructed upon multi modal control framework, where the flight trajectories are decomposed to sequences of maneuver modes and associated parameters. Maneuver generation algorithm, makes use of mode transition rules and agility metric graphs to derive feasible maneuver parameters for each mode and overall sequence. Resulting integrated system; tested on simulations for 3D complex environments, gives satisfactory results and promises successful real time implementation.
Emre Koyuncu, N. Kemal Ure, Gokhan Inalhan

A Cost Effective Tracking System for Small Unmanned Aerial Systems

In this work we address the problem of object tracking in a largely unknown dynamic environment under the additional constraint of real-time operation and limited computational power. The main design directives remain that of real time execution and low price, high availability components. It is in a sense an investigation for the minimum required hardware and algorithmic complexity to accomplish the desired tasks. We present a system that is based on simple techniques such as template matching adapted for use in a dynamically changing environment. After development, the system was evaluated as to its suitability in a traffic monitoring application where it demonstrated adequate performance.
Michail Kontitsis, Kimon Valavanis

Vision-Based Road-Following Using Proportional Navigation

This paper describes a new approach for autonomous road following for an unmanned air vehicle (UAV) using a visual sensor. A road is defined as any continuous, extended, curvilinear feature, which can include city streets, highways, and dirt roads, as well as forest-fire perimeters, shorelines, and fenced borders. To achieve autonomous road-following, this paper utilizes Proportional Navigation as the basis for the guidance law, where visual information is directly fed back into the controller. The tracking target for the Proportional Navigation algorithm is chosen as the position on the edge of the camera frame at which the road flows into the image. Therefore, each frame in the video stream only needs to be searched on the edge of the frame, thereby significantly reducing the computational requirements of the computer vision algorithms. The tracking error defined in the camera reference frame shows that the Proportional Navigation guidance law results in a steady-state error caused by bends and turns in the road, which are perceived as road motion. The guidance algorithm is therefore adjusted using Augmented Proportional Navigation Guidance to account for the perceived road accelerations and to force the steady-state error to zero. The effectiveness of the solution is demonstrated through high-fidelity simulations, and with flight tests using a small autonomous UAV.
Ryan S. Holt, Randal W. Beard

A Vision-Based Automatic Landing Method for Fixed-Wing UAVs

In this paper, a vision-based landing system for small-size fixed-wing unmanned aerial vehicles (UAVs) is presented. Since a single GPS without a differential correction typically provide position accuracy of at most a few meters, an airplane equipped with a single GPS only is not guaranteed to land at a designated location with a sufficient accuracy. Therefore, a visual servoing algorithm is proposed to improve the accuracy of landing. In this scheme, the airplane is controlled to fly into the visual marker by directly feeding back the pitch and yaw deviation angles sensed by the forward-looking camera during the terminal landing phase. The visual marker is a monotone hemispherical airbag, which serves as the arresting device while providing a strong and yet passive visual cue for the vision system. The airbag is detected by using color- and moment-based target detection methods. The proposed idea was tested in a series of experiments using a blended wing-body airplane and proven to be viable for landing of small fixed-wing UAVs.
Sungsik Huh, David Hyunchul Shim

A Vision-Based Guidance System for UAV Navigation and Safe Landing using Natural Landmarks

In this paper a vision-based approach for guidance and safe landing of an Unmanned Aerial Vehicle (UAV) is proposed. The UAV is required to navigate from an initial to a final position in a partially known environment. The guidance system allows a remote user to define target areas from a high resolution aerial or satellite image to determine either the waypoints of the navigation trajectory or the landing area. A feature-based image-matching algorithm finds the natural landmarks and gives feedbacks to an onboard, hierarchical, behaviour-based control system for autonomous navigation and landing. Two algorithms for safe landing area detection are also proposed, based on a feature optical flow analysis. The main novelty is in the vision-based architecture, extensively tested on a helicopter, which, in particular, does not require any artificial landmark (e.g., helipad). Results show the appropriateness of the vision-based approach, which is robust to occlusions and light variations.
A. Cesetti, E. Frontoni, A. Mancini, P. Zingaretti, S. Longhi

Autonomous Vision-Based Helicopter Flights Through Obstacle Gates

The challenge for unmanned aerial vehicles to sense and avoid obstacles becomes even harder if narrow passages have to be crossed. An approach to solve a mission scenario that tackles the problem of such narrow passages is presented here. The task is to fly an unmanned helicopter autonomously through a course with gates that are only slightly larger than the vehicle itself. A camera is installed on the vehicle to detect the gates. Using vehicle localization data from a navigation solution, camera alignment and global gate positions are estimated simultaneously. The presented algorithm calculates the desired target waypoints to fly through the gates. Furthermore, the paper presents a mission execution plan that instructs the vehicle to search for a gate, to fly through it after successful detection, and to search for a proceeding one. All algorithms are designed to run onboard the vehicle so that no interaction with the ground control station is necessary,making the vehicle completely autonomous. To develop and optimize algorithms, and to prove the correctness and accuracy of vision-based gate detection under real operational conditions, gate positions are searched in images taken from manual helicopter flights. Afterwards, the integration of visual sensing and mission control is proven. The paper presents results from full autonomous flight where the helicopter searches and flies through a gate without operator actions.
Franz Andert, Florian-M. Adolf, Lukas Goormann, Jörg S. Dittrich

Exploring the Effect of Obscurants on Safe Landing Zone Identification

Manned rotorcraft are often employed in harsh environments and difficult terrain that are inaccessible to other craft. Conversely, robotic rotorcraft are operated in controlled settings, often at safe, high altitudes. Missions such as cargo delivery, medevac and fire fighting are unachievable because of unpredictable adverse environmental conditions. To enable UAVs to perform these missions, the effects of obscurants on UAV sensor suites and algorithms must be clearly understood. This paper explores the use of a laser range finder to accomplish landing zone identification in unknown, unstructured environments. The ability to detect a landing zone in environments obscured by smoke is investigated. This is accomplished using a design methodology of testing and evaluating in a controlled environment followed by verification and validation in the field. This methodology establishes a concrete understanding of the sensor performance, thereby removing ambiguities in field tests.
Keith W. Sevcik, Noah Kuntz, Paul Y. Oh

Low-Cost Visual Tracking of a Landing Place and Hovering Flight Control with a Microcontroller

The growth of civil and military use has recently promoted the development of unmanned miniature aerial vehicles dedicated to surveillance tasks. These flying vehicles are often capable of carrying only a few dozen grammes of payload. To achieve autonomy for this kind of aircraft novel sensors are required, which need to cope with strictly limited onboard processing power. One of the key aspects in autonomous behaviour is target tracking. Our visual tracking approach differs from other methods by not using expensive cameras but a Wii remote camera, i.e. commodity consumer hardware. The system works without stationary sensors and all processing is done with an onboard microcontroller. The only assumptions are a good roll and pitch attitude estimation, provided by an inertial measurement unit and a stationary pattern of four infrared spots on the target or the landing spot. This paper details experiments for hovering above a landing place, but tracking a slowly moving target is also possible.
Karl E. Wenzel, Paul Rosset, Andreas Zell

Landing and Perching on Vertical Surfaces with Microspines for Small Unmanned Air Vehicles

We present the first results of a system that allows small fixed-wing UAVs to land and cling on surfaces such as brick walls using arrays of microspines that engage asperities on the surface. The requirements of engaging and loading the spines lead to an approach in which an open-loop pitch-up motion is triggered by a range sensor as the plane nears the wall. The subsequent dynamics result in a period during which the plane stays within an envelope of acceptable orientation and velocity (pitch from 60–105 deg, vertical velocity from 0 to −2.7 m/s and up to 3 m/s of horizontal velocity) that permit successful perching. At touchdown, a non-linear suspension absorbs the remaining kinetic energy to minimize peak forces, prevents bouncing and facilitates spine engagement. The total maneuver duration is less than 1 s. We describe the spine suspension and its analysis and present results of typical perching maneuvers (10 landings under autonomous control and 20 under manual control). Under calm conditions, the success rate for autonomous perching on building walls is approximately 80%, the failures being attributed to erroneous wall detection. We conclude with a discussion of future work to increase the robustness of the approach (e.g. with wind) and allow subsequent take-offs to resume flight.
Alexis Lussier Desbiens, Mark R. Cutkosky

Automating Human Thought Processes for a UAV Forced Landing

This paper describes the current status of a program to develop an automated forced landing system for a fixed-wing Unmanned Aerial Vehicle (UAV). This automated system seeks to emulate human pilot thought processes when planning for and conducting an engine-off emergency landing. Firstly, a path planning algorithm that extends Dubins curves to 3D space is presented. This planning element is then combined with a nonlinear guidance and control logic, and simulated test results demonstrate the robustness of this approach to strong winds during a glided descent. The average path deviation errors incurred are comparable to or even better than that of manned, powered aircraft. Secondly, a study into suitable multi-criteria decision making approaches and the problems that confront the decision-maker is presented. From this study, it is believed that decision processes that utilize human expert knowledge and fuzzy logic reasoning are most suited to the problem at hand, and further investigations will be conducted to identify the particular technique/s to be implemented in simulations and field tests. The automated UAV forced landing approach presented in this paper is promising, and will allow the progression of this technology from the development and simulation stages through to a prototype system.
Pillar Eng, Luis Mejias, Xi Liu, Rodney Walker

Autonomous Autorotation of Unmanned Rotorcraft using Nonlinear Model Predictive Control

Safe operations of unmanned rotorcraft hinge on successfully accommodating failures during flight, either via control reconfiguration or by terminating flight early in a controlled manner. This paper focuses on autorotation, a common maneuver used to bring helicopters safely to the ground even in the case of loss of power to the main rotor. A novel nonlinear model predictive controller augmented with a recurrent neural network is presented that is capable of performing an autonomous autorotation. Main advantages of the proposed approach are on-line, real-time trajectory optimization and reduced hardware requirements.
Konstantinos Dalamagkidis, Kimon P. Valavanis, Les A. Piegl

Multimodal Interface Technologies for UAV Ground Control Stations

A Comparative Analysis
This paper examines different technologies that can be applied in the design and development of a ground control station for Unmanned Aerial Vehicles (UAVs) equipped with multimodal interfaces. Multimodal technologies employ multiple sensory channels/modalities for information transmission as well as for system control. Examples of these technologies could be haptic feedback, head tracking, auditory information (3D audio), voice control, tactile displays, etc. The applicability and benefits of those technologies is analyzed for a task consisting in the acknowledgement of alerts in an UAV ground control station composed by three screens and managed by a single operator. For this purpose, several experiments were conducted with a group of individuals using different combinations of modal conditions (visual, aural and tactile).
I. Maza, F. Caballero, R. Molina, N. Peña, A. Ollero

Multi-UAV Simulator Utilizing X-Plane

This paper describes the development of a simulator for multiple Unmanned Aerial Vehicles (UAVs) utilizing the commercially available simulator XPlane and Matlab. Coordinated control of unmanned systems is currently being researched for a wide range of applications, including search and rescue, convoy protection, and building clearing to name a few. Although coordination and control of Unmanned Ground Vehicles (UGVs) has been a heavily researched area, the extension towards controlling multiple UAVs has seen minimal attention. This lack of development is due to numerous issues including the difficulty in realistically modeling and simulating multiple UAVs. This work attempts to overcome these limitations by creating an environment that can simultaneously simulate multiple air vehicles as well as provide state data and control input for the individual vehicles using a heavily developed and commercially available flight simulator (X-Plane). This framework will allow researchers to study multi-UAV control algorithms using realistic unmanned and manned aircraft models in real-world modeled environments. Validation of the system’s ability is shown through the demonstration of formation control algorithms implemented on four UAV helicopters with formation and navigation controllers built in Matlab/Simulink.
Richard Garcia, Laura Barnes

UAS Flight Simulation with Hardware-in-the-loop Testing and Vision Generation

UAS flight simulation for research and development is a difficult problem because each airframe requires accurate physical models, control systems, an organized method of testing new control systems, virtual cameras for vision-based control, and methods of testing new control in the transition from simulation to flight tests. In an environment where researchers are temporary, such as a university, a standard research and development platform with these properties expedites prototyping and prevents code loss when an employee leaves. We develop a research simulation which conforms to all of these properties inside a Matlab environment. A series of mex functions provide connections to the autopilot for hardware-in-the-loop testing, graphical interfaces, and vision processing. The option to write C mex functions offers a seamless method of porting code to embedded systems, minimizing coding errors. We demonstrate fast prototyping by showing flight test data where the simulation provided virtual vision data to avoid virtual obstacles.
Jeffery Saunders, Randal Beard

Multi-UAV Cooperation and Control for Load Transportation and Deployment

This paper deals with the cooperation and control of multiple UAVs with sensing and actuation capabilities. An architecture to perform cooperative missions with a multi-UAV platform is presented. The interactions between UAVs are not only information exchanges but also physical couplings required to cooperate in the joint transportation of a single load. Then, the paper also presents the control system for the transportation of a slung load by means of one or several helicopters. Experimental results of the load transportation system with one and three helicopters are shown. On the other hand, the UAVs considered in the platform can also deploy small objects, such as sensor nodes, on different locations if it is required. This feature along with the whole platform architecture are illustrated in the paper with a real multi-UAV mission for the deployment of sensor nodes to repair the connectivity of a wireless sensor network.
I. Maza, K. Kondak, M. Bernard, A. Ollero

Flyphone: Visual Self-Localisation Using a Mobile Phone as Onboard Image Processor on a Quadrocopter

An unmanned aerial vehicle (UAV) needs to orient itself in its operating environment to fly autonomously. Localisation methods based on visual data are independent of erroneous GPS measurements or imprecise inertial sensors. In our approach, a quadrocopter first establishes an image database of the environment. Afterwards, the quadrocopter is able to locate itself by comparing a current image taken of the environment with earlier images in the database. Therefore, characteristic image features are extracted which can be compared efficiently. We analyse three feature extraction methods and five feature similarity measures. The evaluation is based on two datasets recorded under real conditions. The computations are performed on a Nokia N95 mobile phone, which is mounted on the quadrocopter. This lightweight, yet powerful device offers an integrated camera and serves as central processing unit. The mobile phone proved to be a good choice for visual localisation on a quadrocopter.
Sara Erhard, Karl E. Wenzel, Andreas Zell

A Rotary-wing Unmanned Air Vehicle for Aquatic Weed Surveillance and Management

This paper addresses the novel application of an autonomous rotary-wing unmanned air vehicle (RUAV) as a cost-effective tool for the surveillance and management of aquatic weeds. A conservative estimate of the annual loss of agricultural revenue to the Australian economy due to weeds is in the order of A$4 billion, hence the reason why weed control is of national significance. The presented system locates and identifies weeds in inaccessible locations. The RUAV is equipped with low-cost sensor suites and various weed detection algorithms. In order to provide the weed control operators with the capability of autonomous or remote control spraying and treatment of the aquatic weeds the RUAV is also fitted with a spray mechanism. The system has been demonstrated over inaccessible weed infested aquatic habitats.
Ali Haydar Göktoğan, Salah Sukkarieh, Mitch Bryson, Jeremy Randle, Todd Lupton, Calvin Hung

Development and Evaluation of a Chase View for UAV Operations in Cluttered Environments

Civilian applications for UAVs will bring these vehicles into low flying areas cluttered with obstacles such as building, trees, power lines, and more importantly civilians. The high accident rate of UAVs means that civilian use will come at a huge risk unless we design systems and protocols that can prevent UAV accidents, better train operators and augment pilot performance. This paper presents two methods for generating a chase view to the pilot for UAV operations in cluttered environments. The chase view gives the operator a virtual view from behind the UAV during flight. This is done by generating a virtual representation of the vehicle and surrounding environment while integrating it with the real-time onboard camera images. Method I presents a real-time mapping approach toward generating the surrounding environment and Method II uses a prior model of the operating environment. Experimental results are presented from tests where subjects flew in a H0 scale environment using a 6 DOF gantry system. Results showed that the chase view improved UAV operator performance over using the traditional onboard camera view.
James T. Hing, Keith W. Sevcik, Paul Y. Oh

Design Methodology of a Hybrid Propulsion Driven Electric Powered Miniature Tailsitter Unmanned Aerial Vehicle

Contrary to the manned tailsitter aircraft concepts, which have been shelved and forgotten after mid 1960’s, the unmanned versions of these concepts have become popular. Since, tailsitter type UAVs combine both vertical takeoff and landing (VTOL) operation and relatively high speed cruise flight capabilities which provide manifest advantages over the other VTOL aircraft concepts, including helicopters and organic air vehicles (OAVs). However, there is no mini class tailsitter UAV with efficient high speed cruise flight capability. This paper presents the design methodology and optimization of ITU Tailsitter UAV concept with hybrid propulsion system approach to fill that gap. The initial design and analysis show the advantageous performance over other mini-class VTOL UAVs.
Mirac Aksugur, Gokhan Inalhan
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