34,183 research outputs found
Symmetry-Based Search Space Reduction For Grid Maps
In this paper we explore a symmetry-based search space reduction technique
which can speed up optimal pathfinding on undirected uniform-cost grid maps by
up to 38 times. Our technique decomposes grid maps into a set of empty
rectangles, removing from each rectangle all interior nodes and possibly some
from along the perimeter. We then add a series of macro-edges between selected
pairs of remaining perimeter nodes to facilitate provably optimal traversal
through each rectangle. We also develop a novel online pruning technique to
further speed up search. Our algorithm is fast, memory efficient and retains
the same optimality and completeness guarantees as searching on an unmodified
grid map
Coverage, Continuity and Visual Cortical Architecture
The primary visual cortex of many mammals contains a continuous
representation of visual space, with a roughly repetitive aperiodic map of
orientation preferences superimposed. It was recently found that orientation
preference maps (OPMs) obey statistical laws which are apparently invariant
among species widely separated in eutherian evolution. Here, we examine whether
one of the most prominent models for the optimization of cortical maps, the
elastic net (EN) model, can reproduce this common design. The EN model
generates representations which optimally trade of stimulus space coverage and
map continuity. While this model has been used in numerous studies, no
analytical results about the precise layout of the predicted OPMs have been
obtained so far. We present a mathematical approach to analytically calculate
the cortical representations predicted by the EN model for the joint mapping of
stimulus position and orientation. We find that in all previously studied
regimes, predicted OPM layouts are perfectly periodic. An unbiased search
through the EN parameter space identifies a novel regime of aperiodic OPMs with
pinwheel densities lower than found in experiments. In an extreme limit,
aperiodic OPMs quantitatively resembling experimental observations emerge.
Stabilization of these layouts results from strong nonlocal interactions rather
than from a coverage-continuity-compromise. Our results demonstrate that
optimization models for stimulus representations dominated by nonlocal
suppressive interactions are in principle capable of correctly predicting the
common OPM design. They question that visual cortical feature representations
can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure
CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization
Localization is an essential component for autonomous robots. A
well-established localization approach combines ray casting with a particle
filter, leading to a computationally expensive algorithm that is difficult to
run on resource-constrained mobile robots. We present a novel data structure
called the Compressed Directional Distance Transform for accelerating ray
casting in two dimensional occupancy grid maps. Our approach allows online map
updates, and near constant time ray casting performance for a fixed size map,
in contrast with other methods which exhibit poor worst case performance. Our
experimental results show that the proposed algorithm approximates the
performance characteristics of reading from a three dimensional lookup table of
ray cast solutions while requiring two orders of magnitude less memory and
precomputation. This results in a particle filter algorithm which can maintain
2500 particles with 61 ray casts per particle at 40Hz, using a single CPU
thread onboard a mobile robot.Comment: 8 pages, 14 figures, ICRA versio
Methods of Hierarchical Clustering
We survey agglomerative hierarchical clustering algorithms and discuss
efficient implementations that are available in R and other software
environments. We look at hierarchical self-organizing maps, and mixture models.
We review grid-based clustering, focusing on hierarchical density-based
approaches. Finally we describe a recently developed very efficient (linear
time) hierarchical clustering algorithm, which can also be viewed as a
hierarchical grid-based algorithm.Comment: 21 pages, 2 figures, 1 table, 69 reference
The circumstellar disk of HH 30. Searching for signs of disk evolution with multi-wavelength modeling
Circumstellar disks are characteristic for star formation and vanish during
the first few Myr of stellar evolution. During this time planets are believed
to form in the dense midplane by growth, sedimentation and aggregation of dust.
Indicators of disk evolution, such as holes and gaps, can be traced in the
spectral energy distribution (SED) and spatially resolved images.
We aim to construct a self-consistent model of HH 30 by fitting all available
continuum observations simultaneously. New data sets not available in previous
studies, such as high-resolution interferometric imaging with the Plateau de
Bure Interferometer (PdBI) at lambda = 1.3 mm and SED measured with IRS on the
Spitzer Space Telescope in the mid-infrared, put strong constraints on
predictions and are likely to provide new insights into the evolutionary state
of this object.
A parameter study based on simulated annealing was performed to find unbiased
best-fit models for independent observations made in the wavelength domain
lambda ~ 1 micron ... 4 mm. The method essentially creates a Markov chain
through parameter space by comparing predictions generated by our
self-consistent continuum radiation transfer code MC3D with observations.
We present models of the edge-on circumstellar disk of HH 30 based on
observations from the near-infrared to mm-wavelengths that suggest the presence
of an inner depletion zone with about 45 AU radius and a steep decline of mm
opacity beyond 140 AU. Our modeling indicates that several modes of dust
evolution such as growth, settling, and radial migration are taking place in
this object.
High-resolution observations of HH 30 at different wavelengths with
next-generation observatories such as ALMA and JWST will enable the modeling of
inhomogeneous dust properties and significantly expand our understanding of
circumstellar disk evolution.Comment: Accepted for publication in Astronomy and Astrophysic
Complexity in surfaces of densest packings for families of polyhedra
Packings of hard polyhedra have been studied for centuries due to their
mathematical aesthetic and more recently for their applications in fields such
as nanoscience, granular and colloidal matter, and biology. In all these
fields, particle shape is important for structure and properties, especially
upon crowding. Here, we explore packing as a function of shape. By combining
simulations and analytic calculations, we study three 2-parameter families of
hard polyhedra and report an extensive and systematic analysis of the densest
packings of more than 55,000 convex shapes. The three families have the
symmetries of triangle groups (icosahedral, octahedral, tetrahedral) and
interpolate between various symmetric solids (Platonic, Archimedean, Catalan).
We find that optimal (maximum) packing density surfaces that reveal unexpected
richness and complexity, containing as many as 130 different structures within
a single family. Our results demonstrate the utility of thinking of shape not
as a static property of an object in the context of packings, but rather as but
one point in a higher dimensional shape space whose neighbors in that space may
have identical or markedly different packings. Finally, we present and
interpret our packing results in a consistent and generally applicable way by
proposing a method to distinguish regions of packings and classify types of
transitions between them.Comment: 16 pages, 8 figure
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