Helicopter Autonomous Ship Landing System

This research focuses on developing a helicopter autonomous ship landing algorithm based on the real helicopter ship landing procedure which is already proven and currently used by Navy pilots. It encompasses the entire ship landing procedure from approach to landing using a pilot-inspired vision-based navigation system. The present thesis focuses on the first step towards achieving this overarching objective, which involves modeling the flight dynamics and control of a helicopter and some preliminary simulations of a UH-60 (Blackhawk) helicopter landing on a ship. The airframe of the helicopter is modeled as a rigid body along with rotating articulated blades that can undergo flap, lag and pitch motions about the root. A UH-60 helicopter is used for a representative model due to its ample simulation and flight test data. Modeling a UH-60 helicopter is based on Blade Element Momentum Theory (BEMT), rotor aerodynamics with the Pitt-Peters linear inflow model, empennage aerodynamics and rigid body dynamics for fuselage. For the blade dynamics, the cyclic (1/rev) and collective pitch motions are prescribed and the blade (1/rev) flap and lag motions are obtained as a response to the aerodynamic and inertial forces. The helicopter control inputs and translational and attitude dynamics obtained from the model are validated with flight test data at various speeds and attitude. A linearized model is extracted based on a first-order Taylor series expansion of the nonlinear system about an equilibrium point for the purpose of determining the stability of the dynamic system, investigating sensitivity to gusts, and designing a model-based flight control system. Combined vision-based navigation and Linear Quadratic Regulator (LQR) for set-point tracking is used for disturbance rejection and tracking states. A rotatable camera is used for identifying the relative position of the helicopter with respect to the ship. Based on the position, a corresponding trajectory is computed. Considering the trade-off between transient responses and control efforts, gains for the LQR controller are chosen carefully and realistically. A fully autonomous flight is simulated from approach to landing on a ship. It consists of initial descent, steady forward flight, steady coordinated turn, deceleration, and final landing. Corresponding to each maneuver, relevant linearized model is used and gains are tuned. By using X-plane flight simulator program, the simulation data which include fuselage attitude and position at each time step are visualized with a single flight deck ship. This method allows an aircraft to land on a ship autonomously while maintaining high level of safety and accuracy without the need to capture the ship deck motions, however, by using a camera, and any other additional sensors, which will provide the accurate location of the ship relative to the helicopter. This method is not only relevant for a particular helicopter, but for any types of VTOL aircraft, manned or unmanned. Hence, it can improve the level of safety by preventing human errors that may occur during landing on a ship

Helicopter Autonomous Ship Landing System

This research focuses on developing a helicopter autonomous ship landing algorithm based on the real helicopter ship landing procedure which is already proven and currently used by Navy pilots. It encompasses the entire ship landing procedure from approach to landing using a pilot-inspired vision-based navigation system. The present thesis focuses on the first step towards achieving this overarching objective, which involves modeling the flight dynamics and control of a helicopter and some preliminary simulations of a UH-60 (Blackhawk) helicopter landing on a ship. The airframe of the helicopter is modeled as a rigid body along with rotating articulated blades that can undergo flap, lag and pitch motions about the root. A UH-60 helicopter is used for a representative model due to its ample simulation and flight test data. Modeling a UH-60 helicopter is based on Blade Element Momentum Theory (BEMT), rotor aerodynamics with the Pitt-Peters linear inflow model, empennage aerodynamics and rigid body dynamics for fuselage. For the blade dynamics, the cyclic (1/rev) and collective pitch motions are prescribed and the blade (1/rev) flap and lag motions are obtained as a response to the aerodynamic and inertial forces. The helicopter control inputs and translational and attitude dynamics obtained from the model are validated with flight test data at various speeds and attitude. A linearized model is extracted based on a first-order Taylor series expansion of the nonlinear system about an equilibrium point for the purpose of determining the stability of the dynamic system, investigating sensitivity to gusts, and designing a model-based flight control system. Combined vision-based navigation and Linear Quadratic Regulator (LQR) for set-point tracking is used for disturbance rejection and tracking states. A rotatable camera is used for identifying the relative position of the helicopter with respect to the ship. Based on the position, a corresponding trajectory is computed. Considering the trade-off between transient responses and control efforts, gains for the LQR controller are chosen carefully and realistically. A fully autonomous flight is simulated from approach to landing on a ship. It consists of initial descent, steady forward flight, steady coordinated turn, deceleration, and final landing. Corresponding to each maneuver, relevant linearized model is used and gains are tuned. By using X-plane flight simulator program, the simulation data which include fuselage attitude and position at each time step are visualized with a single flight deck ship. This method allows an aircraft to land on a ship autonomously while maintaining high level of safety and accuracy without the need to capture the ship deck motions, however, by using a camera, and any other additional sensors, which will provide the accurate location of the ship relative to the helicopter. This method is not only relevant for a particular helicopter, but for any types of VTOL aircraft, manned or unmanned. Hence, it can improve the level of safety by preventing human errors that may occur during landing on a ship

Helicopter Autonomous Ship Landing System

This research focuses on developing a helicopter autonomous ship landing algorithm based on the real helicopter ship landing procedure which is already proven and currently used by Navy pilots. It encompasses the entire ship landing procedure from approach to landing using a pilot-inspired vision-based navigation system. The present thesis focuses on the first step towards achieving this overarching objective, which involves modeling the flight dynamics and control of a helicopter and some preliminary simulations of a UH-60 (Blackhawk) helicopter landing on a ship. The airframe of the helicopter is modeled as a rigid body along with rotating articulated blades that can undergo flap, lag and pitch motions about the root. A UH-60 helicopter is used for a representative model due to its ample simulation and flight test data. Modeling a UH-60 helicopter is based on Blade Element Momentum Theory (BEMT), rotor aerodynamics with the Pitt-Peters linear inflow model, empennage aerodynamics and rigid body dynamics for fuselage. For the blade dynamics, the cyclic (1/rev) and collective pitch motions are prescribed and the blade (1/rev) flap and lag motions are obtained as a response to the aerodynamic and inertial forces. The helicopter control inputs and translational and attitude dynamics obtained from the model are validated with flight test data at various speeds and attitude. A linearized model is extracted based on a first-order Taylor series expansion of the nonlinear system about an equilibrium point for the purpose of determining the stability of the dynamic system, investigating sensitivity to gusts, and designing a model-based flight control system. Combined vision-based navigation and Linear Quadratic Regulator (LQR) for set-point tracking is used for disturbance rejection and tracking states. A rotatable camera is used for identifying the relative position of the helicopter with respect to the ship. Based on the position, a corresponding trajectory is computed. Considering the trade-off between transient responses and control efforts, gains for the LQR controller are chosen carefully and realistically. A fully autonomous flight is simulated from approach to landing on a ship. It consists of initial descent, steady forward flight, steady coordinated turn, deceleration, and final landing. Corresponding to each maneuver, relevant linearized model is used and gains are tuned. By using X-plane flight simulator program, the simulation data which include fuselage attitude and position at each time step are visualized with a single flight deck ship. This method allows an aircraft to land on a ship autonomously while maintaining high level of safety and accuracy without the need to capture the ship deck motions, however, by using a camera, and any other additional sensors, which will provide the accurate location of the ship relative to the helicopter. This method is not only relevant for a particular helicopter, but for any types of VTOL aircraft, manned or unmanned. Hence, it can improve the level of safety by preventing human errors that may occur during landing on a ship

Experimental Studies Towards Understanding the Aeromechanics of a Flexible Robotic Hummingbird Wing in Hover

This study investigated the aeroelastic mechanics of a flexible flapping wing designed and implemented on a two-winged, flapping wing, robotic hummingbird capable of hovering. The investigation focused first on measuring aerodynamic and inertial forces and using these results to quantify efficiency; second, on measuring vertical inertial forces on the flexible flapping wing for the first time using Digital Image Correlation; and three, on quantifying the flowfield using Particle Image Velocimetry at the 70% spanwise location of the wing. The purpose of these experiments was to optimize the lift generation and increase the efficiency of the hover-capable robotic hummingbird. A bench-top experimental setup was designed and developed which flapped a duplicate of the wing used in the actual flying vehicle, and utilized the same flapping kinematics. This setup allowed for the variation of flapping parameters, as well as measurement of performance metrics through sensors which measured the instantaneous lift, torque, flap angle, and current draw. The results found that 108° flapping amplitude at 20 Hz was the most power efficient. This is the first time instantaneous vertical force and torque measurements have been successfully conducted on a flexible, hover capable flapping wing used on a flying vehicle. Additionally, this study calculates vertical inertial loads for the same type of wing using deflection measurements. Results from this investigation can be used for further refinement and structural tuning of flexible flapping wing design for hovering flight

Helicopter Autonomous Ship Landing System

This research focuses on developing a helicopter autonomous ship landing algorithm based on the real helicopter ship landing procedure which is already proven and currently used by Navy pilots. It encompasses the entire ship landing procedure from approach to landing using a pilot-inspired vision-based navigation system. The present thesis focuses on the first step towards achieving this overarching objective, which involves modeling the flight dynamics and control of a helicopter and some preliminary simulations of a UH-60 (Blackhawk) helicopter landing on a ship. The airframe of the helicopter is modeled as a rigid body along with rotating articulated blades that can undergo flap, lag and pitch motions about the root. A UH-60 helicopter is used for a representative model due to its ample simulation and flight test data. Modeling a UH-60 helicopter is based on Blade Element Momentum Theory (BEMT), rotor aerodynamics with the Pitt-Peters linear inflow model, empennage aerodynamics and rigid body dynamics for fuselage. For the blade dynamics, the cyclic (1/rev) and collective pitch motions are prescribed and the blade (1/rev) flap and lag motions are obtained as a response to the aerodynamic and inertial forces. The helicopter control inputs and translational and attitude dynamics obtained from the model are validated with flight test data at various speeds and attitude. A linearized model is extracted based on a first-order Taylor series expansion of the nonlinear system about an equilibrium point for the purpose of determining the stability of the dynamic system, investigating sensitivity to gusts, and designing a model-based flight control system. Combined vision-based navigation and Linear Quadratic Regulator (LQR) for set-point tracking is used for disturbance rejection and tracking states. A rotatable camera is used for identifying the relative position of the helicopter with respect to the ship. Based on the position, a corresponding trajectory is computed. Considering the trade-off between transient responses and control efforts, gains for the LQR controller are chosen carefully and realistically. A fully autonomous flight is simulated from approach to landing on a ship. It consists of initial descent, steady forward flight, steady coordinated turn, deceleration, and final landing. Corresponding to each maneuver, relevant linearized model is used and gains are tuned. By using X-plane flight simulator program, the simulation data which include fuselage attitude and position at each time step are visualized with a single flight deck ship. This method allows an aircraft to land on a ship autonomously while maintaining high level of safety and accuracy without the need to capture the ship deck motions, however, by using a camera, and any other additional sensors, which will provide the accurate location of the ship relative to the helicopter. This method is not only relevant for a particular helicopter, but for any types of VTOL aircraft, manned or unmanned. Hence, it can improve the level of safety by preventing human errors that may occur during landing on a ship

Visual Odometry using Convolutional Neural Networks

Visual odometry is the process of tracking an agent\u27s motion over time using a visual sensor. The visual odometry problem has only been recently solved using traditional, non-machine learning techniques. Despite the success of neural networks at many related problems such as object recognition, feature detection, and optical flow, visual odometry still has not been solved with a deep learning technique. This paper attempts to implement several Convolutional Neural Networks to solve the visual odometry problem and compare slight variations in data preprocessing. The work presented is a step toward reaching a legitimate neural network solution

Robust Reinforcement Learning Algorithm for Vision-based Ship Landing of UAVs

This paper addresses the problem of developing an algorithm for autonomous ship landing of vertical take-off and landing (VTOL) capable unmanned aerial vehicles (UAVs), using only a monocular camera in the UAV for tracking and localization. Ship landing is a challenging task due to the small landing space, six degrees of freedom ship deck motion, limited visual references for localization, and adversarial environmental conditions such as wind gusts. We first develop a computer vision algorithm which estimates the relative position of the UAV with respect to a horizon reference bar on the landing platform using the image stream from a monocular vision camera on the UAV. Our approach is motivated by the actual ship landing procedure followed by the Navy helicopter pilots in tracking the horizon reference bar as a visual cue. We then develop a robust reinforcement learning (RL) algorithm for controlling the UAV towards the landing platform even in the presence of adversarial environmental conditions such as wind gusts. We demonstrate the superior performance of our algorithm compared to a benchmark nonlinear PID control approach, both in the simulation experiments using the Gazebo environment and in the real-world setting using a Parrot ANAFI quad-rotor and sub-scale ship platform undergoing 6 degrees of freedom (DOF) deck motion

Incorporating video into Google MSV

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 52).Mobile Street View is a compelling application but suffers from significant latency problems, especially in limited bandwidth circumstances. Currently, the application uses static images to display street level information. Utilizing video in addition to images has the potential to improve the Street View user experience. In this paper, we examine the design and performance of mobile Street View and consider how to use video to reduce user visible latency. Video also allows for alternate navigation methods which could improve the application's ease of use. We created a prototype on Android to examine the plausibility of incorporating video into mobile Street View. Comparing the performance of our video prototype to the traditional step-by-step Street View approach, we found a 4x increase in the speed of viewing an entire street. For the video prototype I also found significant improvement in both user visible latencies and useful screen time. Additionally, I found that the time to fetch video chunks was less than the time to display them.by Christina Wright.M.Eng