939 resultados para Autonomous ships


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Vol. 2 has title: England's improvement by sea and land. The second part : Containing, I. An account of its scituation, and the growths, and manufactures thereof. II. The benefit and necessity of a voluntary-register. III. A method for improving the Royal-navy, lessening the growing power of France, and obtaining the fishery. IV. Advantageous proposals for the city of London, for the preventing of fires therein; and for lessening the great charge of the trained bands. V. The way to make New-Haven in Sussex, fit to receive ships of burthen. VI. Seasonable discourses of the tin, iron, linnen, and woollen trades; with advantageous proposals for improving them all : Illustrated with seven large copper-plates / By Andrew Yarranton, gent. London : Printed, to be sold by Tho. Parkhurst ..., 1698.

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Mode of access: Internet.

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Title vignette. Printed in red and black, by D.B. Updike, The Merrymount Press.

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Thesis (Master's)--University of Washington, 2016-06

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NASA is working on complex future missions that require cooperation between multiple satellites or rovers. To implement these systems, developers are proposing and using intelligent and autonomous systems. These autonomous missions are new to NASA, and the software development community is just learning to develop such systems. With these new systems, new verification and validation techniques must be used. Current techniques have been developed based on large monolithic systems. These techniques have worked well and reliably, but do not translate to the new autonomous systems that are highly parallel and nondeterministic.

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To navigate successfully in a novel environment a robot needs to be able to Simultaneously Localize And Map (SLAM) its surroundings. The most successful solutions to this problem so far have involved probabilistic algorithms, but there has been much promising work involving systems based on the workings of part of the rodent brain known as the hippocampus. In this paper we present a biologically plausible system called RatSLAM that uses competitive attractor networks to carry out SLAM in a probabilistic manner. The system can effectively perform parameter self-calibration and SLAM in onedimension. Tests in two dimensional environments revealed the inability of the RatSLAM system to maintain multiple pose hypotheses in the face of ambiguous visual input. These results support recent rat experimentation that suggest current competitive attractor models are not a complete solution to the hippocampal modelling problem.