124 research outputs found

    Preliminary Study Using Forward Reaction Control System Jets During Space Shuttle Entry

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    Failure or degradation of the flight control system, or hull damage, can lead to loss of vehicle control during entry. Possible failure scenarios are debris impact and wing damage that could result in a large aerodynamic asymmetry which cannot be trimmed out without additional yaw control. Currently the space shuttle uses aerodynamic control surfaces and Reaction Control System jets to control attitude. The forward jets are used for orbital maneuvering only, while the aft jets are used for yaw control during entry. This paper develops a controller for using the forward reaction control system jets as an additional control during entry, and assesses its value and feasibility during failure situations. Forward-aft jet blending logic is created, and implemented on a simplified model of the space shuttle entry flight control system. The model is validated and verified on the nonlinear, six degree-of-freedom Shuttle Engineering Simulator. A rudimentary human factors study was undertaken using the forward cockpit simulator at Johnson Space Center, to assess flying qualities of the new system and pilot workload. Results presented in the paper show that the combination of forward and aft jets provides useful additional yaw control, in addition to potential fuel savings and the ability to balance the use of the fuel in the forward and aft tanks to meet availability constraints of both forward and aft fuel tanks. Piloted simulation studies indicated that using both sets of jets while flying a damaged space shuttle reduces pilot workload, and makes the vehicle more responsive

    Methodology for Prototyping Increased Levels of Automation for Spacecraft Rendezvous Functions

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    The Crew Exploration Vehicle necessitates higher levels of automation than previous NASA vehicles, due to program requirements for automation, including Automated Rendezvous and Docking. Studies of spacecraft development often point to the locus of decision-making authority between humans and computers (i.e. automation) as a prime driver for cost, safety, and mission success. Therefore, a critical component in the Crew Exploration Vehicle development is the determination of the correct level of automation. To identify the appropriate levels of automation and autonomy to design into a human space flight vehicle, NASA has created the Function-specific Level of Autonomy and Automation Tool. This paper develops a methodology for prototyping increased levels of automation for spacecraft rendezvous functions. This methodology is used to evaluate the accuracy of the Function-specific Level of Autonomy and Automation Tool specified levels of automation, via prototyping. Spacecraft rendezvous planning tasks are selected and then prototyped in Matlab using Fuzzy Logic techniques and existing Space Shuttle rendezvous trajectory algorithms

    An investigation of fighter aircraft agility

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    This report attempts to unify in a single document the results of a series of studies on fighter aircraft agility funded by the NASA Ames Research Center, Dryden Flight Research Facility and conducted at the University of Kansas Flight Research Laboratory during the period January 1989 through December 1993. New metrics proposed by pilots and the research community to assess fighter aircraft agility are collected and analyzed. The report develops a framework for understanding the context into which the various proposed fighter agility metrics fit in terms of application and testing. Since new metrics continue to be proposed, this report does not claim to contain every proposed fighter agility metric. Flight test procedures, test constraints, and related criteria are developed. Instrumentation required to quantify agility via flight test is considered, as is the sensitivity of the candidate metrics to deviations from nominal pilot command inputs, which is studied in detail. Instead of supplying specific, detailed conclusions about the relevance or utility of one candidate metric versus another, the authors have attempted to provide sufficient data and analyses for readers to formulate their own conclusions. Readers are therefore ultimately responsible for judging exactly which metrics are 'best' for their particular needs. Additionally, it is not the intent of the authors to suggest combat tactics or other actual operational uses of the results and data in this report. This has been left up to the user community. Twenty of the candidate agility metrics were selected for evaluation with high fidelity, nonlinear, non real-time flight simulation computer programs of the F-5A Freedom Fighter, F-16A Fighting Falcon, F-18A Hornet, and X-29A. The information and data presented on the 20 candidate metrics which were evaluated will assist interested readers in conducting their own extensive investigations. The report provides a definition and analysis of each metric; details of how to test and measure the metric, including any special data reduction requirements; typical values for the metric obtained using one or more aircraft types; and a sensitivity analysis if applicable. The report is organized as follows. The first chapter in the report presents a historical review of air combat trends which demonstrate the need for agility metrics in assessing the combat performance of fighter aircraft in a modern, all-aspect missile environment. The second chapter presents a framework for classifying each candidate metric according to time scale (transient, functional, instantaneous), further subdivided by axis (pitch, lateral, axial). The report is then broadly divided into two parts, with the transient agility metrics (pitch lateral, axial) covered in chapters three, four, and five, and the functional agility metrics covered in chapter six. Conclusions, recommendations, and an extensive reference list and biography are also included. Five appendices contain a comprehensive list of the definitions of all the candidate metrics; a description of the aircraft models and flight simulation programs used for testing the metrics; several relations and concepts which are fundamental to the study of lateral agility; an in-depth analysis of the axial agility metrics; and a derivation of the relations for the instantaneous agility and their approximations

    Efficiently Combining Human Demonstrations and Interventions for Safe Training of Autonomous Systems in Real-Time

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    This paper investigates how to utilize different forms of human interaction to safely train autonomous systems in real-time by learning from both human demonstrations and interventions. We implement two components of the Cycle-of-Learning for Autonomous Systems, which is our framework for combining multiple modalities of human interaction. The current effort employs human demonstrations to teach a desired behavior via imitation learning, then leverages intervention data to correct for undesired behaviors produced by the imitation learner to teach novel tasks to an autonomous agent safely, after only minutes of training. We demonstrate this method in an autonomous perching task using a quadrotor with continuous roll, pitch, yaw, and throttle commands and imagery captured from a downward-facing camera in a high-fidelity simulated environment. Our method improves task completion performance for the same amount of human interaction when compared to learning from demonstrations alone, while also requiring on average 32% less data to achieve that performance. This provides evidence that combining multiple modes of human interaction can increase both the training speed and overall performance of policies for autonomous systems.Comment: 9 pages, 6 figure

    Unmanned aerial systems-based remote sensing for monitoring sorghum growth and development

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    Unmanned Aerial Vehicles and Systems (UAV or UAS) have become increasingly popular in recent years for agricultural research applications. UAS are capable of acquiring images with high spatial and temporal resolutions that are ideal for applications in agriculture. The objective of this study was to evaluate the performance of a UAS-based remote sensing system for quantification of crop growth parameters of sorghum (Sorghum bicolor L.) including leaf area index (LAI), fractional vegetation cover (fc) and yield. The study was conducted at the Texas A&M Research Farm near College Station, Texas, United States. A fixed-wing UAS equipped with a multispectral sensor was used to collect image data during the 2016 growing season (April±October). Flight missions were successfully carried out at 50 days after planting (DAP; 25 May), 66 DAP (10 June) and 74 DAP (18 June). These flight missions provided image data covering the middle growth period of sorghum with a spatial resolution of approximately 6.5 cm. Field measurements of LAI and fc were also collected. Four vegetation indices were calculated using the UAS images. Among those indices, the normalized difference vegetation index (NDVI) showed the highest correlation with LAI, fc and yield with R2 values of 0.91, 0.89 and 0.58 respectively. Empirical relationships between NDVI and LAI and between NDVI and fc were validated and proved to be accurate for estimating LAI and fc from UAS-derived NDVI values. NDVI determined from UAS imagery acquired during the flowering stage (74 DAP) was found to be the most highly correlated with final grain yield. The observed high correlations between UAS-derived NDVI and the crop growth parameters (fc, LAI and grain yield) suggests the applicability of UAS for withinseason data collection of agricultural crops such as sorghum

    Transformers for Lunar Extreme Environments: Ensuring Long-Term Operations in Regions of Darkness and Low Temperatures

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    This report shows how solar power could enable robotic operations in permanently shaded regions at lunar poles, to extract water ice and further produce liquid hydrogen and oxygen (LH2/LO2) propellant. The power needs are derived from an Architecture for Human Exploration of Mars based entirely on lunar propellant. The extraction of 10 metric tons of water per day (at 10% water in regolith) requires approx. 0.6 MW thermal power. Additional approx. 2 MW electric power are required to produce 7.5 metric tons of LH2/LO2 propellant per day, as needed by the architecture. To provide power to processing equipment inside Shackleton Crater, optimal locations are determined on the crater rim, from which several reflecting TransFormers (TFs) would redirect sunlight, achieving a combined period of illumination of approx. 99% of the year. A single 40-m diameter reflector could provide up to 1 MW solar power. Inflatable rigidizable tower support structures raise reflectors above ground for better solar exposure. There are trade-offs: e.g., two reflectors at ground level would provide the same combined total illumination as a single tower approx. 100-m tall. Such a TF based on a 100-m tower made with inflatable 2-m beams and 40-m diameter reflectors would be of similar dimensions as an MSL-class rover (approx. 1000 kg, 10 m(exp 3)). A TF-prospector rover combo could be designed and deployed in a Discovery-class mission searching for water. The TransFormers would be nodes of a Lunar Utilities Infrastructure that provides solar power year-round in the proximity of the pole, as well as local data transmission andintermittent direct to earth communications. This infrastructure would be instrumental infacilitating the development of a lunar economy
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