19 research outputs found

    Metalevel Motion Planning for Unmanned Aircraft Systems: Metrics Definition and Algorithm Selection

    Full text link
    A diverse suite of manned and unmanned aircraft will occupy future urban airspace. Flight plans must accommodate specific aircraft characteristics, including physical volume with safety zone clearance, landing/takeoff procedures, kinodynamics, and a wide range of flight environments. No single motion planner is applicable across all possible aircraft configurations and operating conditions. This dissertation proposes the first motion planning algorithm selection capability with application to small Unmanned Aircraft System (UAS) multicopters operating in and over a complex urban landscape. Alternative data-driven fail-safe protocols are presented to improve on contemporary ``fly-home'' or automatic landing protocols, focusing on rooftops as safe urban landing sites. In a fail-safe direct strategy, the multicopter identifies, generates, and follows a flight plan to the closest available rooftop suitable for landing. In a fail-safe supervisory strategy, the multicopter examines rooftops en route to a planned landing site, diverting to a closer, clear landing site when possible. In a fail-safe coverage strategy, the multicopter cannot preplan a safe landing site due to missing data. The multicopter executes a coverage path to explore the area and evaluate overflown rooftops to find a safe landing site. These three fail-safe algorithms integrate map generation, flight planning, and area coverage capabilities. The motion planning algorithm selection problem (ASP) requires qualitative and quantitative metrics to inform the ASP of user/agent, algorithm, and configuration space preferences and constraints. Urban flight map-based, path-based, and software-based cost metrics are defined to provide insights into the urban canyon properties needed to construct safe and efficient flight plans. Map-based metrics describe the operating environment by constructing a collection of GPS/Lidar navigation performance, population density, and obstacle risk exposure metric maps. Path-based metrics account for a vehicle's energy consumption and distance traveled. Software-based metrics measure memory consumption and execution time of an algorithm. The proposed metrics provide pre-flight insights typically ignored by obstacle-only planning environment definitions. An algorithm portfolio consisting of geometric (Point-to-Point: PTP), graph-based (A* variants), and sampling-based (BIT* variants) motion planners were considered in this work. Path cost, execution time, and success rate benchmarks were investigated using Monte Carlo problem instances with A* "plus" producing the lowest cost paths, PTP having the fastest executions, and A* "dist" having the best overall success rates. The BIT* variant paths typically had higher cost but their success rate increased relative to altitude. The problem instances and metric maps informed two new machine learning solutions for urban small UAS motion planning ASP. Rule-based decision trees were simple to construct but unable to capture both complex cost metrics and algorithm properties. The investigated neural network-based ASP formulations produced promising results, with a hybrid two-stage selection scheme having the best algorithm selection accuracy, laying the seeds for future work. The most significant innovation of this dissertation is motion planning ASP for UAS. Non-traditional open-source databases also advance the field of data-driven flight planning, contributing to fail-safe UAS operations as well as ASP. Path planning algorithms integrated a new suite of diverse cost metrics accompanied by a novel multi-objective admissible heuristic function. Neural network and decision tree ASP options were presented and evaluated as a first-case practical approach to solving the motion planning ASP for small UAS urban flight.PHDRoboticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168060/1/cosme_1.pd

    3D-in-2D Displays for ATC.

    Get PDF
    This paper reports on the efforts and accomplishments of the 3D-in-2D Displays for ATC project at the end of Year 1. We describe the invention of 10 novel 3D/2D visualisations that were mostly implemented in the Augmented Reality ARToolkit. These prototype implementations of visualisation and interaction elements can be viewed on the accompanying video. We have identified six candidate design concepts which we will further research and develop. These designs correspond with the early feasibility studies stage of maturity as defined by the NASA Technology Readiness Level framework. We developed the Combination Display Framework from a review of the literature, and used it for analysing display designs in terms of display technique used and how they are combined. The insights we gained from this framework then guided our inventions and the human-centered innovation process we use to iteratively invent. Our designs are based on an understanding of user work practices. We also developed a simple ATC simulator that we used for rapid experimentation and evaluation of design ideas. We expect that if this project continues, the effort in Year 2 and 3 will be focus on maturing the concepts and employment in a operational laboratory settings

    Using MapReduce Streaming for Distributed Life Simulation on the Cloud

    Get PDF
    Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

    Safety and Reliability - Safe Societies in a Changing World

    Get PDF
    The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen

    Pertanika Journal of Science & Technology

    Get PDF

    Aeronautical engineering: A continuing bibliography with indexes (supplement 254)

    Get PDF
    This bibliography lists 538 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
    corecore