About: Flight computer is a research topic. Over the lifetime, 227 publications have been published within this topic receiving 2665 citations. The topic is also known as: whiz wheel.
TL;DR: In this article, the authors present the first realistic demonstration of a complete guidance, navigation and control (GNC) system for formation flying spacecraft in low Earth orbit, which is used in the TanDEM-X formation flying mission.
Abstract: Formation flying is commonly identified as the collective usage of two or more cooperative spacecraft to exercise the function of a single monolithic virtual instrument. The distribution of tasks and payloads among fleets of coordinated smaller satellites offers the possibility to overcome the classical limitations of traditional single-satellite systems. The science return is enhanced through observations made with larger, configurable baselines and an improved degree of redundancy can be achieved in the event of failures. Different classes of formation flying missions are currently under discussion within the engineering and science community: technology demonstration missions, synthetic aperture interferometers and gravimeters for Earth observation, multi-spacecraft interferometers in the infrared and visible wavelength regions as a key to new astrophysics discoveries and to the direct search for terrestrial exoplanets. These missions are characterized by different levels of complexity, mainly dictated by the payload metrology and actuation needs, and require a high level of on-board autonomy to satisfy the continuously increasing demand of relative navigation and control accuracy. This dissertation presents the first realistic demonstration of a complete guidance, navigation and control (GNC) system for formation flying spacecraft in low Earth orbit. Numerous technical contributions have been made during the course of this research in the areas of formation flying guidance, GPS-based relative navigation, and impulsive relative orbit control, but the primary contribution of this thesis does not lie in one or more of these disciplines. The innovation and originality of this work stems from the design and implementation of a comprehensive formation flying system through the successful integration of various techniques. This research has led to the full development, testing and validation of the GNC flight code to be embedded in the on-board computer of the active spacecraft of the PRISMA technology demonstration. Furthermore key guidance and control algorithms presented here are going to be demonstrated for the first time in the TanDEM-X formation flying mission. Overall this thesis focuses on realistic application cases closely related to upcoming missions. The intention is to realize a practical and reliable way to formation flying: a technology that is discussed and studied since decades but is still confined in research laboratories. Hardware-in-the-loop real-time simulations including a representative flight computer and the GPS hardware architecture show that simple techniques, which exploit the natural orbit motion to full extent, can meet the demanding requirements of long-term close formation-flying.
TL;DR: The prototype is a Quadrotor weighing approximately 600g, with a diameter of 550mm, which carries the necessary electronics for stability control, altitude control, collision avoidance and anti-drift control.
Abstract: This paper presents a Miniature Aerial Vehicle (MAV) capable of hands- off autonomous operation within indoor environments. Our prototype is a Quadrotor weighing approximately 600g, with a diameter of 550mm, which carries the necessary electronics for stability control, altitude control, collision avoidance and anti-drift control. This MAV is equipped with three rate gyroscopes, three accelerometers, one ultrasonic sensor, four infrared sensors, a high-speed motor controller and a flight computer. Autonomous flight tests have been carried out in a 7x6-m room.
TL;DR: In this paper, an unmanned aerial vehicle and associated methods for inspecting infrastructure assets includes a multi-rotor, electrically driven helicopter apparatus and power supply; a flight computer; positioning and collision avoidance equipment; and at least one sensor such as a camera.
Abstract: An unmanned aerial vehicle and associated methods for inspecting infrastructure assets includes a multirotor, electrically driven helicopter apparatus and power supply; a flight computer; positioning and collision avoidance equipment; and at least one sensor such as a camera. The flight computer is programmed for automated travel to and inspection of selected waypoints, at which condition data is collected for further analysis. The method also includes protocols for segmenting the flight path to accomplish sequential inspection of a linear asset such as a power line using limited-range equipment.
TL;DR: The GTMax testbed developed at the Georgia Institute of Technology UAV research facility allows for a variety of onboard sensors, supports reconfiguration, and has the capability to demonstrate aggressive maneuvers under complex and changing mission scenarios.
Abstract: Autonomous unmanned aerial vehicles (UAVs) require avionics systems that enable them to maintain a stable attitude and to follow a desired flight path. This paper considers the design and development of such an avionics system that provides navigational and terrain information to the flight computer of a rotorcraft UAV. The process includes the design and testing of flight hardware and software that interprets sensor data. The paper provides an overview of a specific implementation of the approach: the GTMax testbed developed at the Georgia Institute of Technology UAV research facility. Its available payload and performance allows for a variety of onboard sensors, supports reconfiguration, and has the capability to demonstrate aggressive maneuvers under complex and changing mission scenarios.
TL;DR: A neural network is proposed as an approach to the task of failure detection following damage to an aerodynamic surface of an aircraft flight control system, and the identification of the damage type can be achieved.
Abstract: In this paper, a neural network is proposed as an approach to the task of failure detection following damage to an aerodynamic surface of an aircraft flight control system. Several drawbacks of other failure detection techniques can be avoided by taking advantage of the flexible learning and generalization capabilities of a neural network. This structure, used for state estimation purposes, can be designed and trained on line in flight and generates a residual signal indicating the damage as soon as it occurs. From an analysis of the cross-correlation functions between some key state variables, the identification of the damage type can also be achieved. The results of a nonlinear numerical simulation for a damaged control surface are reported and discussed.