Offshore Drone Logistics Optimization and Corporate Feasibility

Drones can help offshore logistics to improve safety, increase production efficiency, and reduce CO2 emissions. Drones will also be used in the development of new energy solutions on offshore stations. The aim is to see new logistics and support infrastructure, which will complement what we now have on ships and helicopters. Johan Castberg FPSO requires offshore drone logistics operations and for that purpose literature review on the history and types of drones is done to establish a multi-criteria system. Based on that multi-criteria system a drone fleet with different ranges and payload capacities is established. Keeping an eye on the advanced and upcoming drone technologies that can boost the use of drones in offshore logistics different power sources are discussed. To fulfill the objectives of offshore drone logistics in a pre-operational and operational phase different challenges have been discussed in this thesis project that includes type of logistics model in the supply chain, loading and unloading mechanisms with human safety and Environmental parameters, Operational and maintenance regime, and feasibility analysis of the implementation of drone logistics. All these pre-operational and operational phase challenges are discussed in detail and solutions to different challenges are proposed

Maximizing Accuracy through Stereo Vision Camera Positioning for Automated Aerial Refueling

Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. The analysis focuses on the effects of camera positioning with the rear-facing stereo vision system. In particular, the research seeks the optimal system design for the camera system to achieve the most accurate navigational estimates. The testing process consists of utilizing a simulation engine and recreating real world flights based on previously collected Global Positioning System (GPS) data. Using the pose estimation results and the ground truth information, the system computes the error between the incoming aircraft\u27s position in the virtual world and its calculated location based on the stereo matching algorithm. The testing process includes both un-obscured scenarios and cases where the boom causes significant occlusions in the camera images. The results define the improvements in position and orientation estimation of camera positioning from the consolidated simulation data. Conclusions drawn from this research will propose and help provide recommendations for future Air Force acquisition and development of aerial refueling systems

Technology challenges of stealth unmanned combat aerial vehicles

The ever-changing battlefield environment, as well as the emergence of global command and control architectures currently used by armed forces around the globe, requires the use of robust and adaptive technologies integrated into a reliable platform. Unmanned Combat Aerial Vehicles (UCAVs) aim to integrate such advanced technologies while also increasing the tactical capabilities of combat aircraft. This paper provides a summary of the technical and operational design challenges specific to UCAVs, focusing on high-performance, and stealth designs. After a brief historical overview, the main technology demonstrator programmes currently under development are presented. The key technologies affecting UCAV design are identified and discussed. Finally, this paper briefly presents the main issues related to airworthiness, navigation, and ethical concerns behind UAV/UCAV operations

Autonomous ground refuelling approach for civil aircrafts using computer vision and robotics

3D visual servoing systems need to detect the object and its pose in order to perform. As a result accurate, fast object detection and pose estimation play a vital role. Most visual servoing methods use low-level object detection and pose estimation algorithms. However, many approaches detect objects in 2D RGB sequences for servoing, which lacks reliability when estimating the object’s pose in 3D space. To cope with these problems, firstly, a joint feature extractor is employed to fuse the object’s 2D RGB image and 3D point cloud data. At this point, a novel method called PosEst is proposed to exploit the correlation between 2D and 3D features. Here are the results of the custom model using test data; precision: 0,9756, recall: 0.9876, F1 Score(beta=1): 0.9815, F1 Score(beta=2): 0.9779. The method used in this study can be easily implemented to 3D grasping and 3D tracking problems to make the solutions faster and more accurate. In a period where electric vehicles and autonomous systems are gradually becoming a part of our lives, this study offers a safer, more efficient and more comfortable environment

Wake vortex modelling and simulation for air vehicles in close formation flight

The aim of this research is to develop realistic models of aerodynamic cross-coupling effects that can be incorporated in real-time or near real-time simulations of Unmanned Aerial Vehicles (UAVs) in close formation flight. These would permit the assessment of the risks and issues associated with wake vortex evolution and encounter and the analysis of their consequences on the design of automatic control systems and the development of safe and reliable operating procedures. A number of wake vortex modelling techniques that can be used in formation flight simulations are reviewed. A novel Wake Vortex Model (WVM) is developed, implemented, verified, validated and successfully integrated within a Matlab/Simulink simulation environment. The code, named ELL because it is based on Weissinger’s extended lifting line theory, meets the following requirements: (i) it is generic and can easily be adapted to accomodate any wing planform and air vehicle configuration; (ii) it is computationally rapid enough to be used in real-time or near real-time simulations; (iii) and it is sufficiently representative to support studies of aerodynamic interaction between multiple air vehicles during formation reconfiguration and air-to-air refuelling simulations. Simulink test scenarios of two Aerosonde UAVs are developed to test and validate the use of ELL within simulation models, and the simulation environment is interfaced with visualisation tools in order to facilitate the evaluation of multiple air vehicle dynamic interaction.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Infrared and Electro-Optical Stereo Vision for Automated Aerial Refueling

Currently, Unmanned Aerial Vehicles are unsafe to refuel in-flight due to the communication latency between the UAVs ground operator and the UAV. Providing UAVs with an in-flight refueling capability would improve their functionality by extending their flight duration and increasing their flight payload. Our solution to this problem is Automated Aerial Refueling (AAR) using stereo vision from stereo electro-optical and infrared cameras on a refueling tanker. To simulate a refueling scenario, we use ground vehicles to simulate a pseudo tanker and pseudo receiver UAV. Imagery of the receiver is collected by the cameras on the tanker and processed by a stereo block matching algorithm to calculate a position and orientation estimate of the receiver. GPS and IMU truth data is then used to validate these results

Machine vision and scientific imaging for autonomous air vehicles (UAV).

This thesis outlines the necessary requirements to determine an Unmanned Aerial Vehicles (UAV’s) pose relative to a lead aircraft or target, thus enabling a UAV to successfully follow a lead aircraft or target. The use of Machine Vision for Autonomous navigation has been investigated and two flight scenarios were chosen for analysis. Firstly, following a manoeuvring lead aircraft, and secondly, maintaining a steady heading behind a target/lead aircraft (as would be required for in-flight refuelling). In addition, the author has performed a literature review of current research in this field which is significantly dominated by eventual military requirements in order to improve UAV endurance. In addition, experimental work towards developing a passive vision based navigation system has been undertaken. It is hoped that after further research and development this will lead to an eventual flight trial using the flight dynamics department’s UAV’s. The experimental work has been performed using both equipment and software already available within the department and furthermore, it has enabled an analysis of the department’s currently available capabilities for passive visual navigation to be undertaken. Key points for further work have been outlined for the future advancement of the visual navigation project.Engineering and Physical Sciences (EPSRC)MSc in Aerospace Dynamic

Modeling and nonlinear adaptive control of an aerial manipulation system

Autonomous aerial robots have become an essential part of many civilian and military applications. The workspace and agility of these vehicles motivated great research interest resulting in various studies addressing their control architectures and mechanical configurations. Increasing autonomy enabled them to perform tasks such as surveillance, inspection and remote sensing in hazardous and challenging environments. The ongoing research promises further contributions to the society, in both theory and practice. To furthermore extend their vast applications, aerial robots are equipped with the tools to enable physical interaction with the environment. These tasks represent a great challenge due to the technological limitations as well as the lack of sophisticated methods necessary for the control of the system to perform desired operations in an efficient and stable manner. Modeling and control problem of an aerial manipulation is still an open research topic with many studies addressing these issues from different perspectives. This thesis deals with the nonlinear adaptive control of an aerial manipulation system (AMS). The system consists of a quadrotor equipped with a 2 degrees of freedom (DOF) manipulator. The complete modeling of the system is done using the Euler-Lagrange method. A hierarchical nonlinear control structure which consists of outer and inner control loops has been utilized. Model Reference Adaptive Controller (MRAC) is designed for the outer loop where the required command signals are generated to force the quadrotor to move on a reference trajectory in the presence of mass uncertainties and reaction forces coming from the manipulator. For the inner loop, the attitude dynamics of the quadrotor and the joint dynamics of the 2-DOF robotic arm are considered as a fully actuated 5-DOF unified part of the AMS. Nonlinear adaptive control has been utilized for the low-level controller where the changes in inertias have been considered. The proposed controller is tested on a high fidelity AMS model in the presence of uncertainties, wind disturbances and measurement noise, and satisfactory trajectory tracking performance with improved robustness is achieved