Investigation of advanced navigation and guidance system concepts for all-weather rotorcraft operations

Results are presented of a survey conducted of active helicopter operators to determine the extent to which they wish to operate in IMC conditions, the visibility limits under which they would operate, the revenue benefits to be gained, and the percent of aircraft cost they would pay for such increased capability. Candidate systems were examined for capability to meet the requirements of a mission model constructed to represent the modes of flight normally encountered in low visibility conditions. Recommendations are made for development of high resolution radar, simulation of the control display system for steep approaches, and for development of an obstacle sensing system for detecting wires. A cost feasibility analysis is included

Remote Airport Traffic Control Center (2008 - 2012) Final Presentation and Workshop - Extended Abstracts

The present report contains the extended and revised version of the abstracts collection of the presentations given at the final international workshop of the DLR-project RAiCe (Remote Airport traffic Control Center, 2008 - 2012), held on November 30 2012 in Braunschweig. The RaiCe presentations are complemented by two external contributions,from the Swedish ANSP LFV and company Frequentis, representing the industrial perspective on Remote Tower research and development. The RaiCe workshop was a satellite event of the Second SESAR Innovation Days (SID 2012, Nov. 27-29) which was held in Braunschweig, following the first one in Toulouse 2011. One of the RaiCe validation results papers was presented at SID2012 and is also included in the present report for com-pleteness, besides inclusion in the SID2012 proceedings. In addition to the collection of extended abstracts and an introduction, besides some general refer-ences a list of the publications of the DLR Remote Tower Group (time frame 2002 – 2012) is provid-ed. A list of the workshop participants is added as part of the Appendix

ROADS—Rover for Bituminous Pavement Distress Survey: An Unmanned Ground Vehicle (UGV) Prototype for Pavement Distress Evaluation

Maintenance has a major impact on the financial plan of road managers. To ameliorate road conditions and reduce safety constraints, distress evaluation methods should be efficient and should avoid being time consuming. That is why road cadastral catalogs should be updated periodically, and interventions should be provided for specific management plans. This paper focuses on the setting of an Unmanned Ground Vehicle (UGV) for road pavement distress monitoring, and the Rover for bituminOus pAvement Distress Survey (ROADS) prototype is presented in this paper. ROADS has a multisensory platform fixed on it that is able to collect different parameters. Navigation and environment sensors support a two-image acquisition system which is composed of a high-resolution digital camera and a multispectral imaging sensor. The Pavement Condition Index (PCI) and the Image Distress Quantity (IDQ) are, respectively, calculated by field activities and image computation. The model used to calculate the I-ROADS index from PCI had an accuracy of 74.2%. Such results show that the retrieval of PCI from image-based approach is achievable and values can be categorized as "Good"/"Preventive Maintenance", "Fair"/"Rehabilitation", "Poor"/"Reconstruction", which are ranges of the custom PCI ranting scale and represents a typical repair strategy

Zero/zero rotorcraft certification issues. Volume 2: Plenary session presentations

This report analyzes the Zero/Zero Rotorcraft Certification Issues from the perspectives of manufacturers, operators, researchers and the FAA. The basic premise behind this analysis is that zero/zero, or at least extremely low visibility, rotorcraft operations are feasible today from both a technological and an operational standpoint. The questions and issues that need to be resolved are: What certification requirements do we need to ensure safety. Can we develop procedures which capitalize on the performance and maneuvering capabilities unique to rotorcraft. Will extremely low visibility operations be economically feasible. This is Volume 2 of three. It presents the operator perspectives (system needs), applicable technology and zero/zero concepts developed in the first 12 months of research of this project

Autonomous Capabilities for Small Unmanned Aerial Systems Conducting Radiological Response: Findings from a High-fidelity Discovery Experiment

This article presents a preliminary work domain theory and identifies autonomous vehicle, navigational, and mission capabilities and challenges for small unmanned aerial systems (SUASs) responding to a radiological disaster. Radiological events are representative of applications that involve flying at low altitudes and close proximities to structures. To more formally understand the guidance and control demands, the environment in which the SUAS has to function, and the expected missions, tasks, and strategies to respond to an incident, a discovery experiment was performed in 2013. The experiment placed a radiological source emitting at 10 times background radiation in the simulated collapse of a multistory hospital. Two SUASs, an AirRobot 100B and a Leptron Avenger, were inserted with subject matter experts into the response, providing high operational fidelity. The SUASs were expected by the responders to fly at altitudes between 0.3 and 30 m, and hover at 1.5 m from urban structures. The proximity to a building introduced a decrease in GPS satellite coverage, challenging existing vehicle autonomy. Five new navigational capabilities were identified: scan, obstacle avoidance, contour following, environment-aware return to home, andreturn to highest reading. Furthermore, the data-to-decision process could be improved with autonomous data digestion and visualization capabilities. This article is expected to contribute to a better understanding of autonomy in a SUAS, serve as a requirement document for advanced autonomy, and illustrate how discovery experimentation serves as a design tool for autonomous vehicles

Aeronautical engineering: A continuing bibliography with indexes (supplement 250)

This bibliography lists 420 reports, articles, and other documents introduced into the NASA scientific and technical information system in February, 1990. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

Monitorització d'incendis amb imatges des de satèl·lit i amb UAV

Desenvolupament d'algorisme de detecció d'incendis amb imatge de satèl·lit i validació amb imatges des d'avió.Wildfires are of major concern now days because, even though they have also a natural role, they have negative impacts in environmental, economic and social terms. The main purposes of this project are the study, combination, comparison of different ways to sense fires. It focus on the images and data -that remotely sensed by instruments- provided and transmitted from satellites and drones. Its uttermost purpose is to design ways to detect, trace, measure the burned areas from UAV and give a comprehensive view of the wildfire while it is taking place. It deepens into the nature of forest fires and relates how factors like wind or terrain affect their propagation and growth. In the case of UAV, based on the information received from the sensors at an altitude between 10km and 20km, the project discusses how to measure the burned areas. Despite there is little data or imagery recorded with specific instruments from this altitude while a forest fire is taking place at this stage, it is enough to draw some lines of action. Meanwhile, satellite images and data of forest fires already occurred are easily available, we had no forest fires images recorded by UAVs or other airplanes at 10 or 20km height. Consequently, many algorithm of detection and monitoring using only images from satellite (both when there is no fire and when there is burning a fire) and images from sensors flying on UAVs.. With all that information regarding the sensors and the patterns of the fire it is possible to discern the movements of the fire. Once the movements and growth are recorded and known, a drone-based easy-to-understand chart of the wildfire is delivered.Los incendios constituyen una gran preocupación hoy en dia, a pesar que a veces juegan un papel natural, también tienen un impacto negativo en términos medioambientales, económicos y sociales. Este proyecto consiste en el estudio , la combinación , la comparación de diferentes maneras para detectar, medir y entender los incendios. Se centra en el estudio de las imágenes y datos captados remotamente por sensores -y camaras- desde satélite y desde aviones no tripulados. Su máximo objetivo es diseñar maneras de detectar , rastrear , medir las áreas quemadas y dar una visión comprehensiva de un incendio forestal mientras este tiene lugar. Se profundiza en la naturaleza del fuego durante los incendios forestales y como factores como el viento o el terreno afecta su propagación y crecimiento. Basándose en información recibida desde sensores a una altitud de entre 10km y 20km, el proyecto discute como medir la áreas quemadas. A pesar que no hay muchos datos o imágenes de incendios grabados desde drones a esta altitud con ciertos instrumentos mientras este ocurre, eso es suficiente para plantear unas lineas de estudio y trabajo. Con las características de ciertos sensores y los patrones descritos por el fuego es posible discernir los movimientos del incendio. Una vez grabados y conocidos tales movimientos debería ser posible mostrar un mapa o diagrama del incendio fácil de entender basado en drones para la gente que esta sobre el terreno.Els focs forestals constitueixen una gran preocupació avui en dia, malgrat que a vegades juguen un paper natural, també tenen un impacte negatiu en termes ambientals, econòmics y socials. Aquest projecte consisteix en l'estudi, la combinació , la comparació de diferents maneres per detectar incendis. Es centra en el estudi de images i dades produides i transmeses per sensors desde satel·lits i per avions no tripulats. El seu màxim objectiu és dissenyar maneres de detectar , rastrejar , mesurar les àrees cremades y donar una visión comprensiva d'in incendi forestal mentre aquest es produeix. S'aprofundeix en la naturalesa del foc durant els incendis forestals i com factors com el vent o el terreny afecten la seva propagació i creixement. En el cas dels UAV o drones, basant-se en la informació rebuda des dels sensors a una altitud d'entre 10km i 20km, el projecte discuteix com mesurar les arees cremades. Malgrat que no existeix moltes dades o imatges sobre incendis a aquestes altituts grabades per drones, es suficient per plantejar unes lines d'estudi, treball i acció. Amb les caracteristiques del sensors i els patrons descrits pel foc seria possible discernir els moviments del incendi. Llavors un cop grabats i coneguts aquest creixement hauria de ser possible mostrar un mapa o diagrames utils i fàcils d'entendre basat en drones per a la gent que esta sobre el terreny

A Cooperative Approach for Autonomous Landing of UAVs

This dissertation presents a cooperative approach for the autonomous landing of MRVTOL UAVs (Multi Rotor-Vertical Take-off and Landing Unmanned Aerial Vehicles). Most standard UAV autonomous landing systems take an approach, where the UAV detects a pre-set pattern on the landing zone, establishes relative positions and uses them to perform the landing. These methods present some drawbacks such as all of the processing being performed by the UAV itself, requiring high computational power from it. An additional problem arises from the fact most of these methods are only reliable when the UAV is already at relatively low altitudes since the pattern’s features have to be clearly visible from the UAV’s camera. The method presented throughout this dissertation relies on an RGB camera, placed in the landing zone pointing upwards towards the sky. Due to the fact, the sky is a fairly stagnant and uniform environment the unique motion patterns the UAV displays can be singled out and analysed using Background Subtraction and Optical Flow techniques. A terrestrial or surface robotic system can then analyse the images in real-time and relay commands to the UAV. The result is a model-free method, i.e independent of the UAV’s morphological aspect or pre-determined patterns, capable of aiding the UAV during the landing manoeuvre. The approach is reliable enough to be used as a stand-alone method, or be used along traditional methods achieving a more robust system. Experimental results obtained from a dataset encompassing 23 diverse videos showed the ability of the computer vision algorithm to perform the detection of the UAV in 93,44% of the 44557 evaluated frames with a tracking error of 6.6%. A high-level control system that employs the concept of an approach zone to the helipad was also developed. Within the zone every possible three-dimensional position corresponds to a velocity command for the UAV, with a given orientation and magnitude. The control system was tested in a simulated environment and it proved to be effective in performing the landing of the UAV within 13 cm from the goal

Aeronautical engineering: A continuing bibliography with indexes (supplement 255)

This bibliography lists 529 reports, articles, and other documents introduced into the NASA scientific and technical information system in June 1990. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics

An investigation of change in drone practices in broadacre farming environments

The application of drones in broadacre farming is influenced by novel and emergent factors. Drone technology is subject to legal, financial, social, and technical constraints that affect the Agri-tech sector. This research showed that emerging improvements to drone technology influence the analysis of precision data resulting in disparate and asymmetrically flawed Ag-tech outputs. The novelty of this thesis is that it examines the changes in drone technology through the lens of entropic decay. It considers the planning and controlling of an organisation’s resources to minimise harmful effects through systems change. The rapid advances in drone technology have outpaced the systematic approaches that precision agriculture insists is the backbone of reliable ongoing decision-making. Different models and brands take data from different heights, at different times of the day, and with flight of differing velocities. Drone data is in a state of decay, no longer equally comparable to past years’ harvest and crop data and are now mixed into a blended environment of brand-specific variations in height, image resolution, air speed, and optics. This thesis investigates the problem of the rapid emergence of image-capture technology in drones and the corresponding shift away from the established measurements and comparisons used in precision agriculture. New capabilities are applied in an ad hoc manner as different features are rushed to market. At the same time existing practices are subtly changed to suit individual technology capability. The result is a loose collection of technically superior drone imagery, with a corresponding mismatch of year-to-year agricultural data. The challenge is to understand and identify the difference between uniformly accepted technological advance, and market-driven changes that demonstrate entropic decay. The goal of this research is to identify best practice approaches for UAV deployment for broadacre farming. This study investigated the benefits of a range of characteristics to optimise data collection technologies. It identified widespread discrepancies demonstrating broadening decay on precision agriculture and productivity. The pace of drone development is so rapidly different from mainstream agricultural practices that the once reliable reliance upon yearly crop data no longer shares statistically comparable metrics. Whilst farmers have relied upon decades of satellite data that has used the same optics, time of day and flight paths for many years, the innovations that drive increasingly smarter drone technologies are also highly problematic since they render each successive past year’s crop metrics as outdated in terms of sophistication, detail, and accuracy. In five years, the standardised height for recording crop data has changed four times. New innovations, coupled with new rules and regulations have altered the once reliable practice of recording crop data. In addition, the cost of entry in adopting new drone technology is sufficiently varied that agriculturalists are acquiring multiple versions of different drone UAVs with variable camera and sensor settings, and vastly different approaches in terms of flight records, data management, and recorded indices. Without addressing this problem, the true benefits of optimization through machine learning are prevented from improving harvest outcomes for broadacre farming. The key findings of this research reveal a complex, constantly morphing environment that is seeking to build digital trust and reliability in an evolving global market in the face of rapidly changing technology, regulations, standards, networks, and knowledge. The once reliable discipline of precision agriculture is now a fractured melting pot of “first to market” innovations and highly competitive sellers. The future of drone technology is destined for further uncertainty as it struggles to establish a level of maturity that can return broadacre farming to consistent global outcomes