76,753 research outputs found

    Minimizing the Cost of Team Exploration

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    A group of mobile agents is given a task to explore an edge-weighted graph GG, i.e., every vertex of GG has to be visited by at least one agent. There is no centralized unit to coordinate their actions, but they can freely communicate with each other. The goal is to construct a deterministic strategy which allows agents to complete their task optimally. In this paper we are interested in a cost-optimal strategy, where the cost is understood as the total distance traversed by agents coupled with the cost of invoking them. Two graph classes are analyzed, rings and trees, in the off-line and on-line setting, i.e., when a structure of a graph is known and not known to agents in advance. We present algorithms that compute the optimal solutions for a given ring and tree of order nn, in O(n)O(n) time units. For rings in the on-line setting, we give the 22-competitive algorithm and prove the lower bound of 3/23/2 for the competitive ratio for any on-line strategy. For every strategy for trees in the on-line setting, we prove the competitive ratio to be no less than 22, which can be achieved by the DFSDFS algorithm.Comment: 25 pages, 4 figures, 5 pseudo-code

    NASA Langley Research Center Systems Analysis & Concepts Directorate Participation in the Exploration Systems Architecture Study

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    The NASA Langley Research Center (LaRC) Systems Analysis & Concepts Directorate (SACD) began studying human exploration missions beyond low Earth orbit (LEO) in the year 1999. This included participation in NASA s Decadal Planning Team (DPT), the NASA Exploration Team (NExT), Space Architect studies and Revolutionary Aerospace Systems Concepts (RASC) architecture studies that were used in formulating the new Vision for Space Exploration. In May of 2005, NASA initiated the Exploration Systems Architecture Study (ESAS). The primary outputs of the ESAS activity were concepts and functional requirements for the Crewed Exploration Vehicle (CEV), its supporting launch vehicle infrastructure and identification of supporting technology requirements and investments. An exploration systems analysis capability has evolved to support these functions in the past and continues to evolve to support anticipated future needs. SACD had significant roles in supporting the ESAS study team. SACD personnel performed the liaison function between the ESAS team and the Shuttle/Station Configuration Options Team (S/SCOT), an agency-wide team charged with using the Space Shuttle to complete the International Space Station (ISS) by the end of Fiscal Year (FY) 2010. The most significant of the identified issues involved the ability of the Space Shuttle system to achieve the desired number of flights in the proposed time frame. SACD with support from the Kennedy Space Center performed analysis showing that, without significant investments in improving the shuttle processing flow, that there was almost no possibility of completing the 28-flight sequence by the end of 2010. SACD performed numerous Lunar Surface Access Module (LSAM) trades to define top level element requirements and establish architecture propellant needs. Configuration trades were conducted to determine the impact of varying degrees of segmentation of the living capabilities of the combined descent stage, ascent stage, and other elements. The technology assessment process was developed and implemented by SACD as the ESAS architecture was refined. SACD implemented a rigorous and objective process which included (a) establishing architectural functional needs, (b) collection, synthesis and mapping of technology data, and (c) performing an objective decision analysis resulting in technology development investment recommendations. The investment recommendation provided budget, schedule, and center/program allocations to develop required technologies for the exploration architecture, as well as the identification of other investment opportunities to maximize performance and flexibility while minimizing cost and risk. A summary of the trades performed and methods utilized by SACD for the Exploration Systems Mission Directorate (ESAS) activity is presented along with how SACD is currently supporting the implementation of the Vision for Space Exploration

    Decentralized Exploration in Multi-Armed Bandits

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    We consider the decentralized exploration problem: a set of players collaborate to identify the best arm by asynchronously interacting with the same stochastic environment. The objective is to insure privacy in the best arm identification problem between asynchronous, collaborative, and thrifty players. In the context of a digital service, we advocate that this decentralized approach allows a good balance between the interests of users and those of service providers: the providers optimize their services, while protecting the privacy of the users and saving resources. We define the privacy level as the amount of information an adversary could infer by intercepting the messages concerning a single user. We provide a generic algorithm Decentralized Elimination, which uses any best arm identification algorithm as a subroutine. We prove that this algorithm insures privacy, with a low communication cost, and that in comparison to the lower bound of the best arm identification problem, its sample complexity suffers from a penalty depending on the inverse of the probability of the most frequent players. Then, thanks to the genericity of the approach, we extend the proposed algorithm to the non-stationary bandits. Finally, experiments illustrate and complete the analysis

    Efficient Multi-Robot Coverage of a Known Environment

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    This paper addresses the complete area coverage problem of a known environment by multiple-robots. Complete area coverage is the problem of moving an end-effector over all available space while avoiding existing obstacles. In such tasks, using multiple robots can increase the efficiency of the area coverage in terms of minimizing the operational time and increase the robustness in the face of robot attrition. Unfortunately, the problem of finding an optimal solution for such an area coverage problem with multiple robots is known to be NP-complete. In this paper we present two approximation heuristics for solving the multi-robot coverage problem. The first solution presented is a direct extension of an efficient single robot area coverage algorithm, based on an exact cellular decomposition. The second algorithm is a greedy approach that divides the area into equal regions and applies an efficient single-robot coverage algorithm to each region. We present experimental results for two algorithms. Results indicate that our approaches provide good coverage distribution between robots and minimize the workload per robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 201

    Orthogonal-Array based Design Methodology for Complex, Coupled Space Systems

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    The process of designing a complex system, formed by many elements and sub-elements interacting between each other, is usually completed at a system level and in the preliminary phases in two major steps: design-space exploration and optimization. In a classical approach, especially in a company environment, the two steps are usually performed together, by experts of the field inferring on major phenomena, making assumptions and doing some trial-and-error runs on the available mathematical models. To support designers and decision makers during the design phases of this kind of complex systems, and to enable early discovery of emergent behaviours arising from interactions between the various elements being designed, the authors implemented a parametric methodology for the design-space exploration and optimization. The parametric technique is based on the utilization of a particular type of matrix design of experiments, the orthogonal arrays. Through successive design iterations with orthogonal arrays, the optimal solution is reached with a reduced effort if compared to more computationally-intense techniques, providing sensitivity and robustness information. The paper describes the design methodology in detail providing an application example that is the design of a human mission to support a lunar base

    A performance of 2 dimensional ultrasonic vibration assisted milling in cutting force reduction, on aluminium AL6061

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    This paper were investigate a performance of 2 Dimensional Ultrasonic Vibration assisted Milling (UVAM) toward Aluminium Al 6061. The focus is to find the performance of reduction of cutting force compared to the conventional machining in the industries shop floor. Due to the major effect of cutting force of production in industries, the excessive cutting force problem must be investigated deeply as it will cause shortens tool life and reduces the production rate. A scientific approach has been found in order to reduce the cutting force during machining which is integrating the ultrasonic concept into workpiece. The modelling of vibration cutting ratio has been simulated to find the time force contact and non-contact. Thus, less cutting force could be found. The ultrasonic vibration platform that generated by XY25XS from Cedrat Technologies is travelled in X direction as a feed movement. Thus, the X and Y axis vibration actuate along the workpiece for the machining process. The performance of UVAM in cutting force reduction found the superior benefits of UVAM is come from the alternating cycle’s between tool and workpiece. The comparison between UVAM and conventional machining in reduction of cutting force is 32%. The potential of the UVAM tool wear and tool life will be discussed deeply in finding and next in the conclusion section

    ActiveRemediation: The Search for Lead Pipes in Flint, Michigan

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    We detail our ongoing work in Flint, Michigan to detect pipes made of lead and other hazardous metals. After elevated levels of lead were detected in residents' drinking water, followed by an increase in blood lead levels in area children, the state and federal governments directed over $125 million to replace water service lines, the pipes connecting each home to the water system. In the absence of accurate records, and with the high cost of determining buried pipe materials, we put forth a number of predictive and procedural tools to aid in the search and removal of lead infrastructure. Alongside these statistical and machine learning approaches, we describe our interactions with government officials in recommending homes for both inspection and replacement, with a focus on the statistical model that adapts to incoming information. Finally, in light of discussions about increased spending on infrastructure development by the federal government, we explore how our approach generalizes beyond Flint to other municipalities nationwide.Comment: 10 pages, 10 figures, To appear in KDD 2018, For associated promotional video, see https://www.youtube.com/watch?v=YbIn_axYu9
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