151 research outputs found
Planning and Control of Robotic Juggling Tasks
A new class of control algorithms - âmirror algorithmsâ - give rise to experimentally observedjuggling behavior in a simple robotic mechanism. The simplest of these algorithms (upon which all the others are founded) is provably correct with respect to a simplified model of the robot and its environment. This paper reviews the physical setup and underlying mathematical theory, discusses two significant extensions of the fundamental algorithm, provides data from our successful empirical verifications of these control strategies and briefly speculates upon the larger implications for the field of robotics.
For more information: Kod*La
Planning and Control of Robotic Juggling and Catching Tasks
A new class of control algorithmsâthe âmirror algorithmsââ gives rise to experimentally observed juggling and catching behavior in a planar robotic mechanism. The simplest of these algorithms (on which all the others are founded) is provably correct with respect to a simplified model of the robot and its environment. This article briefly reviews the physical setup and underlying mathematical theory. It discusses two significant extensions of the fundamental algorithm to juggling two objects and catching. We provide data from successful empirical verifi cations of these control strategies and briefly speculate on the larger implications for the field of robotics.
For more information: Kod*La
A One Degree of Freedom Juggler in a Two Degree of Freedom Environment
We develop a formalism for describing and analyzing a very simple representative of a class of robotic tasks which require dynamical dexterity, among them the task of juggling. We introduce and report on our preliminary empirical experience with a new class of control algorithms for this task domain that we call mirror algorithms
Generalized Wishart processes for interpolation over diffusion tensor fields
Diffusion Magnetic Resonance Imaging (dMRI) is a non-invasive tool for watching the microstructure of fibrous nerve and muscle tissue. From dMRI, it is possible to estimate 2-rank diffusion tensors imaging (DTI) fields, that are widely used in clinical applications: tissue segmentation, fiber tractography, brain atlas construction, brain conductivity models, among others. Due to hardware limitations of MRI scanners, DTI has the difficult compromise between spatial resolution and signal noise ratio (SNR) during acquisition. For this reason, the data are often acquired with very low resolution. To enhance DTI data resolution, interpolation provides an interesting software solution. The aim of this work is to develop a methodology for DTI interpolation that enhance the spatial resolution of DTI fields. We assume that a DTI field follows a recently introduced stochastic process known as a generalized Wishart process (GWP), which we use as a prior over the diffusion tensor field. For posterior inference, we use Markov Chain Monte Carlo methods. We perform experiments in toy and real data. Results of GWP outperform other methods in the literature, when compared in different validation protocols
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How predation and landscape fragmentation affect vole population dynamics
Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable
populations. The gradient has often been attributed to changes in the interactions between microtines and their predators.
Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species,
it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding
season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating
population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in
the field. The distinction is here attempted using realistic agent-based modelling.
Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and
ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities
whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical
autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of
altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the
presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator
assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the
oscillations.
Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results
allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the
reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape
fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in
future analyses of vole dynamics
Measures in Visualization Space
Postponed access: the file will be available after 2021-08-12Measurement is an integral part of modern science, providing the fundamental means for evaluation, comparison, and prediction. In the context of visualization, several different types of measures have been proposed, ranging from approaches that evaluate particular aspects of visualization techniques, their perceptual characteristics, and even economic factors. Furthermore, there are approaches that attempt to provide means for measuring general properties of the visualization process as a whole. Measures can be quantitative or qualitative, and one of the primary goals is to provide objective means for reasoning about visualizations and their effectiveness. As such, they play a central role in the development of scientific theories for visualization. In this chapter, we provide an overview of the current state of the art, survey and classify different types of visualization measures, characterize their strengths and drawbacks, and provide an outline of open challenges for future research.acceptedVersio
A birdâs eye view: using circuit theory to study urban landscape connectivity for birds
Context
Connectivity is fundamental to understanding how landscape form influences ecological function. However, uncertainties persist due to the difficulty and expense of gathering empirical data to drive or to validate connectivity models, especially in urban areas, where relationships are multifaceted and the habitat matrix cannot be considered to be binary.
Objectives
This research used circuit theory to model urban bird flows (i.e. âcurrentâ), and compared results to observed abundance. The aims were to explore the ability of this approach to predict wildlife flows and to test relationships between modelled connectivity and variation in abundance.
Methods
Circuitscape was used to model functional connectivity in Bedford, Luton/Dunstable, and Milton Keynes, UK, for great tits (Parus major) and blue tits (Cyanistes caeruleus), drawing parameters from published studies of woodland bird flows in urban environments. Model performance was then tested against observed abundance data.
Results
Modelled current showed a weak yet positive agreement with combined abundance for P. major and C. caeruleus. Weaker correlations were found for other woodland species, suggesting the approach may be expandable if re-parameterised.
Conclusions
Trees provide suitable habitat for urban woodland bird species, but their location in large, contiguous patches and corridors along barriers also facilitates connectivity networks throughout the urban matrix. Urban connectivity studies are well-served by the advantages of circuit theory approaches, and benefit from the empirical study of wildlife flows in these landscapes to parameterise this type of modelling more explicitly. Such results can prove informative and beneficial in designing urban green space and new developments
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