31,254 research outputs found

    Project plan for joint FAA/NASA head-up display concept evaluation

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    Head-Up Display (HUD) concept for large commercial turbojet transport aircraft is considered for the its contribution to aviation safety in the form of improved performance during the approach and landing phase flight. The basic reearch areas represent fundamental questions that are still unresolved and which were considered important to the effective use of the HUD by pilots. Project documentation and management responsibilities are outlined

    Multivariate emulation of computer simulators: model selection and diagnostics with application to a humanitarian relief model

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    We present a common framework for Bayesian emulation methodologies for multivariate-output simulators, or computer models, that employ either parametric linear models or nonparametric Gaussian processes. Novel diagnostics suitable for multivariate covariance-separable emulators are developed and techniques to improve the adequacy of an emulator are discussed and implemented. A variety of emulators are compared for a humanitarian relief simulator, modelling aid missions to Sicily after a volcanic eruption and earthquake, and a sensitivity analysis is conducted to determine the sensitivity of the simulator output to changes in the input variables. The results from parametric and nonparametric emulators are compared in terms of prediction accuracy, uncertainty quantification and scientific interpretability

    Graphics simulation and training aids for advanced teleoperation

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    Graphics displays can be of significant aid in accomplishing a teleoperation task throughout all three phases of off-line task analysis and planning, operator training, and online operation. In the first phase, graphics displays provide substantial aid to investigate work cell layout, motion planning with collision detection and with possible redundancy resolution, and planning for camera views. In the second phase, graphics displays can serve as very useful tools for introductory training of operators before training them on actual hardware. In the third phase, graphics displays can be used for previewing planned motions and monitoring actual motions in any desired viewing angle, or, when communication time delay prevails, for providing predictive graphics overlay on the actual camera view of the remote site to show the non-time-delayed consequences of commanded motions in real time. This paper addresses potential space applications of graphics displays in all three operational phases of advanced teleoperation. Possible applications are illustrated with techniques developed and demonstrated in the Advanced Teleoperation Laboratory at JPL. The examples described include task analysis and planning of a simulated Solar Maximum Satellite Repair task, a novel force-reflecting teleoperation simulator for operator training, and preview and predictive displays for on-line operations

    Space Station robotics planning tools

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    The concepts are described for the set of advanced Space Station Freedom (SSF) robotics planning tools for use in the Space Station Control Center (SSCC). It is also shown how planning for SSF robotics operations is an international process, and baseline concepts are indicated for that process. Current SRMS methods provide the backdrop for this SSF theater of multiple robots, long operating time-space, advanced tools, and international cooperation

    ROBOSIM: An intelligent simulator for robotic systems

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    The purpose of this paper is to present an update of an intelligent robotics simulator package, ROBOSIM, first introduced at Technology 2000 in 1990. ROBOSIM is used for three-dimensional geometrical modeling of robot manipulators and various objects in their workspace, and for the simulation of action sequences performed by the manipulators. Geometric modeling of robot manipulators has an expanding area of interest because it can aid the design and usage of robots in a number of ways, including: design and testing of manipulators, robot action planning, on-line control of robot manipulators, telerobotic user interface, and training and education. NASA developed ROBOSIM between 1985-88 to facilitate the development of robotics, and used the package to develop robotics for welding, coating, and space operations. ROBOSIM has been further developed for academic use by its co-developer Vanderbilt University, and has been in both classroom and laboratory environments for teaching complex robotic concepts. Plans are being formulated to make ROBOSIM available to all U.S. engineering/engineering technology schools (over three hundred total with an estimated 10,000+ users per year)

    Collaborative research on V/STOL control system/cockpit display tradeoffs under the NASA/MOD joint aeronautical program

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    Summarized here are activities that have taken place from 1979 to the present in a collaborative program between NASA Ames Research Center and the Royal Aerospace Establishment (now Defence Research Agency), Bedford on flight control system and cockpit display tradeoffs for low-speed and hover operations of future V/STOL aircraft. This program was created as Task 8A of the Joint Aeronautical Program between NASA in the United States and the Ministry of Defence (Procurement Executive) in the United Kingdom. The program was initiated based on a recognition by both parties of the strengths of the efforts of their counterparts and a desire to participate jointly in future simulation and flight experiments. In the ensuing years, teams of NASA and RAE engineers and pilots have participated in each other's simulation experiments to evaluate control and display concepts and define design requirements for research aircraft. Both organizations possess Harrier airframes that have undergone extensive modification to provide in-flight research capabilities in the subject areas. Both NASA and RAE have profited by exchanges of control/display concepts, design criteria, fabrication techniques, software development and validation, installation details, and ground and flight clearance techniques for their respective aircraft. This collaboration has permitted the two organizations to achieve jointly substantially more during the period than if they had worked independently. The two organizations are now entering the phase of flight research for the collaborative program as currently defined

    Flight testing Time and Energy Managed Operations (TEMO)

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    The expected growth in air traffic combined with an increased public concern for the environment, have forced legislators to rethink the current air traffic system design. The current air traffic system operates at its capacity limits and is expected to lead to increased delays if traffic levels grow even further. Both in the United States and Europe, research projects have been initiated to develop the future Air Transportation System (ATS) to address capacity, and environmental, safety and economic issues. To address the environmental issues during descent and approach, a novel Continuous Descent Operations (CDO) concept, named Time and Energy Managed Operations (TEMO), has been developed co-sponsored by the Clean Sky Joint Undertaking. It uses energy principles to reduce fuel burn, gaseous emissions and noise nuisance whilst maintaining runway capacity. Different from other CDO concepts, TEMO optimizes the descent by using energy management to achieve a continuous engine-idle descent, while satisfying time constraints on both the Initial Approach Fix (IAF) and the runway threshold. As such, TEMO uses timemetering at two control points to facilitate flow management and arrival spacing. TEMO is in line with SESAR step 2 capabilities, since it proposes 4D trajectory management and is aimed at providing significant environmental benefits in the arrival phase without negatively affecting throughput, even in high density and peak-hour operations. In particular, TEMO addresses SESAR operational improvement (OI) TS-103: Controlled Time of Arrival (CTA) through use of datalink [1]. TEMO has been validated starting from initial performance batch studies at Technology Readiness Level (TRL) 3, up to Human-in-the-Loop studies in realistic environments using a moving base flight simulator at TRL 5 ([2]-[6]). In this paper the definition, preparation, performance and analysis of a flight test experiment is described with the objective to demonstrate the ability of the TEMO algorithm to provide accurate and safe aircraft guidance toward the Initial Approach Fix (IAF), and further down to the Stabilization Point (1000 ft AGL), to demonstrate the ability of the TEMO algorithm to meet absolute time requirements at IAF and/or runway threshold and to evaluate the performance of the system under test (e.g. fuel usage).Peer ReviewedPostprint (published version

    Learning for Multi-robot Cooperation in Partially Observable Stochastic Environments with Macro-actions

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    This paper presents a data-driven approach for multi-robot coordination in partially-observable domains based on Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) and macro-actions (MAs). Dec-POMDPs provide a general framework for cooperative sequential decision making under uncertainty and MAs allow temporally extended and asynchronous action execution. To date, most methods assume the underlying Dec-POMDP model is known a priori or a full simulator is available during planning time. Previous methods which aim to address these issues suffer from local optimality and sensitivity to initial conditions. Additionally, few hardware demonstrations involving a large team of heterogeneous robots and with long planning horizons exist. This work addresses these gaps by proposing an iterative sampling based Expectation-Maximization algorithm (iSEM) to learn polices using only trajectory data containing observations, MAs, and rewards. Our experiments show the algorithm is able to achieve better solution quality than the state-of-the-art learning-based methods. We implement two variants of multi-robot Search and Rescue (SAR) domains (with and without obstacles) on hardware to demonstrate the learned policies can effectively control a team of distributed robots to cooperate in a partially observable stochastic environment.Comment: Accepted to the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017

    COACHES Cooperative Autonomous Robots in Complex and Human Populated Environments

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    Public spaces in large cities are increasingly becoming complex and unwelcoming environments. Public spaces progressively become more hostile and unpleasant to use because of the overcrowding and complex information in signboards. It is in the interest of cities to make their public spaces easier to use, friendlier to visitors and safer to increasing elderly population and to citizens with disabilities. Meanwhile, we observe, in the last decade a tremendous progress in the development of robots in dynamic, complex and uncertain environments. The new challenge for the near future is to deploy a network of robots in public spaces to accomplish services that can help humans. Inspired by the aforementioned challenges, COACHES project addresses fundamental issues related to the design of a robust system of self-directed autonomous robots with high-level skills of environment modelling and scene understanding, distributed autonomous decision-making, short-term interacting with humans and robust and safe navigation in overcrowding spaces. To this end, COACHES will provide an integrated solution to new challenges on: (1) a knowledge-based representation of the environment, (2) human activities and needs estimation using Markov and Bayesian techniques, (3) distributed decision-making under uncertainty to collectively plan activities of assistance, guidance and delivery tasks using Decentralized Partially Observable Markov Decision Processes with efficient algorithms to improve their scalability and (4) a multi-modal and short-term human-robot interaction to exchange information and requests. COACHES project will provide a modular architecture to be integrated in real robots. We deploy COACHES at Caen city in a mall called “Rive de l’orne”. COACHES is a cooperative system consisting of ?xed cameras and the mobile robots. The ?xed cameras can do object detection, tracking and abnormal events detection (objects or behaviour). The robots combine these information with the ones perceived via their own sensor, to provide information through its multi-modal interface, guide people to their destinations, show tramway stations and transport goods for elderly people, etc.... The COACHES robots will use different modalities (speech and displayed information) to interact with the mall visitors, shopkeepers and mall managers. The project has enlisted an important an end-user (Caen la mer) providing the scenarios where the COACHES robots and systems will be deployed, and gather together universities with complementary competences from cognitive systems (SU), robust image/video processing (VUB, UNICAEN), and semantic scene analysis and understanding (VUB), Collective decision-making using decentralized partially observable Markov Decision Processes and multi-agent planning (UNICAEN, Sapienza), multi-modal and short-term human-robot interaction (Sapienza, UNICAEN
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