642 research outputs found
Optimal Probabilistic Ring Exploration by Asynchronous Oblivious Robots
We consider a team of identical, oblivious, asynchronous mobile robots
that are able to sense (\emph{i.e.}, view) their environment, yet are unable to
communicate, and evolve on a constrained path. Previous results in this weak
scenario show that initial symmetry yields high lower bounds when problems are
to be solved by \emph{deterministic} robots. In this paper, we initiate
research on probabilistic bounds and solutions in this context, and focus on
the \emph{exploration} problem of anonymous unoriented rings of any size. It is
known that robots are necessary and sufficient to solve the
problem with deterministic robots, provided that and are coprime.
By contrast, we show that \emph{four} identical probabilistic robots are
necessary and sufficient to solve the same problem, also removing the coprime
constraint. Our positive results are constructive
First principles calculation of the phonons modes in the hexagonal ferroelectric and paraelectric phases
The lattice dynamics of the magneto-electric compound has been
investigated using density functional calculations, both in the ferroelectric
and the paraelectric phases. The coherence between the computed and
experimental data is very good in the low temperature phase. Using group
theory, modes continuity and our calculations we were able to show that the
phonons modes observed by Raman scattering at 1200K are only compatible with
the ferroelectric space group, thus supporting the idea of a
ferroelectric to paraelectric phase transition at higher temperature. Finally
we proposed a candidate for the phonon part of the observed electro-magnon.
This mode, inactive both in Raman scattering and in Infra-Red, was shown to
strongly couple to the Mn-Mn magnetic interactions
Maximum likelihood estimation and prediction error for a Mat{\'e}rn model on the circle
This work considers Gaussian process interpolation with a periodized version
of the Mat{\'e}rn covariance function (Stein, 1999, Section 6.7) with Fourier
coefficients (^2 + j^2)^(----1/2). Convergence rates are
studied for the joint maximum likelihood estimation of and when
the data is sampled according to the model. The mean integrated squared error
is also analyzed with fixed and estimated parameters, showing that maximum
likelihood estimation yields asymptotically the same error as if the ground
truth was known. Finally, the case where the observed function is a
''deterministic'' element of a continuous Sobolev space is also considered,
suggesting that bounding assumptions on some parameters can lead to different
estimates
Deterministic Rendezvous at a Node of Agents with Arbitrary Velocities
We consider the task of rendezvous in networks modeled as undirected graphs.
Two mobile agents with different labels, starting at different nodes of an
anonymous graph, have to meet. This task has been considered in the literature
under two alternative scenarios: weak and strong. Under the weak scenario,
agents may meet either at a node or inside an edge. Under the strong scenario,
they have to meet at a node, and they do not even notice meetings inside an
edge. Rendezvous algorithms under the strong scenario are known for synchronous
agents. For asynchronous agents, rendezvous under the strong scenario is
impossible even in the two-node graph, and hence only algorithms under the weak
scenario were constructed. In this paper we show that rendezvous under the
strong scenario is possible for agents with restricted asynchrony: agents have
the same measure of time but the adversary can arbitrarily impose the speed of
traversing each edge by each of the agents. We construct a deterministic
rendezvous algorithm for such agents, working in time polynomial in the size of
the graph, in the length of the smaller label, and in the largest edge
traversal time.Comment: arXiv admin note: text overlap with arXiv:1704.0888
Asynchronous approach in the plane: A deterministic polynomial algorithm
In this paper we study the task of approach of two mobile agents having the
same limited range of vision and moving asynchronously in the plane. This task
consists in getting them in finite time within each other's range of vision.
The agents execute the same deterministic algorithm and are assumed to have a
compass showing the cardinal directions as well as a unit measure. On the other
hand, they do not share any global coordinates system (like GPS), cannot
communicate and have distinct labels. Each agent knows its label but does not
know the label of the other agent or the initial position of the other agent
relative to its own. The route of an agent is a sequence of segments that are
subsequently traversed in order to achieve approach. For each agent, the
computation of its route depends only on its algorithm and its label. An
adversary chooses the initial positions of both agents in the plane and
controls the way each of them moves along every segment of the routes, in
particular by arbitrarily varying the speeds of the agents. A deterministic
approach algorithm is a deterministic algorithm that always allows two agents
with any distinct labels to solve the task of approach regardless of the
choices and the behavior of the adversary. The cost of a complete execution of
an approach algorithm is the length of both parts of route travelled by the
agents until approach is completed. Let and be the initial
distance separating the agents and the length of the shortest label,
respectively. Assuming that and are unknown to both agents, does
there exist a deterministic approach algorithm always working at a cost that is
polynomial in and ? In this paper, we provide a positive answer to
the above question by designing such an algorithm
3D Shape Cropping
International audienceWe introduce shape cropping as the segmentation of a bounding geometry of an object as observed by sensors with different modalities. Segmenting a bounding volume is a preliminary step in many multi-view vision applications that consider or require the recovery of 3D information, in particular in multi-camera environments. Recent vision systems used to acquire such information often combine sensors of different types, usually color and depth sensors. Given depth and color images we present an efficient geometric algorithm to compute a polyhedral bounding sur- face that delimits the region in space where the object lies. The resulting cropped geometry eliminates unwanted space regions and enables the initialization of further processes including surface refinements. Our approach ex- ploits the fact that such a region can be defined as the intersection of 3D regions identified as non empty in color or depth images. To this purpose, we propose a novel polyhedron combination algorithm that overcomes compu- tational and robustness issues exhibited by traditional intersection tools in our context. We show the correction and effectiveness of the approach on various combination of inputs
Les bureaux d'Ă©tudes Ă l'Ă©preuve de l'organisation par projet
National audienceDepuis deux décennies, l'organisation du travail par projet, qui vise à accroßtre l'efficacité des entreprises, s'est imposée dans de nombreux secteurs d'activité. Fruit de la remise en cause des modÚles tayloriste et fordiste, elle marque une emprise importante de la dimension gestionnaire et instaure une culture du résultat. Le mode « projet » recourt en effet, de façon intensive, aux outils de gestion et aux techniques de management pour assurer la planification, la coordination, le suivi et la réalisation du travail collectif. L'activité de conception dans les bureaux d'études n'échappe pas à ce mode d'organisation, notamment dans l'industrie aéronautique, qui constitue le cadre de la recherche sur laquelle s'appuie ce Connaissance de l'emploi. Le mode projet entraßne une forte mobilisation et responsabilisation des concepteurs dans un esprit de changement permanent et d'adaptation à ce changement. Il contribue à déstabiliser les collectifs de travail, éphémÚres et soumis à des injonctions contradictoires, et à invisibiliser la coopération et les interactions entre contributeurs
Relaxed Gaussian process interpolation: a goal-oriented approach to Bayesian optimization
This work presents a new procedure for obtaining predictive distributions in
the context of Gaussian process (GP) modeling, with a relaxation of the
interpolation constraints outside some ranges of interest: the mean of the
predictive distributions no longer necessarily interpolates the observed values
when they are outside ranges of interest, but are simply constrained to remain
outside. This method called relaxed Gaussian process (reGP) interpolation
provides better predictive distributions in ranges of interest, especially in
cases where a stationarity assumption for the GP model is not appropriate. It
can be viewed as a goal-oriented method and becomes particularly interesting in
Bayesian optimization, for example, for the minimization of an objective
function, where good predictive distributions for low function values are
important. When the expected improvement criterion and reGP are used for
sequentially choosing evaluation points, the convergence of the resulting
optimization algorithm is theoretically guaranteed (provided that the function
to be optimized lies in the reproducing kernel Hilbert spaces attached to the
known covariance of the underlying Gaussian process). Experiments indicate that
using reGP instead of stationary GP models in Bayesian optimization is
beneficial
Optimal Torus Exploration by Oblivious Robots
International audienceWe consider autonomous robots that are endowed with motion actuators and visibility sensors. The robots we consider are weak, i.e., they are anonymous, uniform, unable to explicitly communicate, and oblivious (they do not remember any of their past actions). In this paper, we propose an optimal (w.r.t. the number of robots) solution for the terminating exploration of a torus-shaped network by a team of such robots. In more details, we first show that it is impossible to explore a simple torus of arbitrary size with (strictly) less than four robots, even if the algorithm is probabilistic. If the algorithm is required to be deterministic, four robots are also insufficient. This negative result implies that the only way to obtain an optimal algorithm (w.r.t. the number of robots participating to the algorithm) is to make use of probabilities. Then, we propose a probabilistic algorithm that uses four robots to explore all simple tori of size , where . Hence, in such tori, four robots are necessary and sufficient to solve the (probabilistic) terminating exploration. As a torus can be seen as a 2-dimensional ring, our result shows, perhaps surprisingly, that increasing the number of possible symmetries in the network (due to increasing dimensions) does not come at an extra cost w.r.t. the number of robots that are necessary to solve the problem
Optimal torus exploration by oblivious robots
International audienceWe deal with a team of autonomous robots that are endowed with motion actuators and visibility sensors. Those robots are weak and evolve in a discrete environment. By weak, we mean that they are anonymous, uniform, unable to explicitly communicate, and oblivious. We first show that it is impossible to solve the terminating exploration of a simple torus of arbitrary size with less than 4 or 5 such robots, respectively depending on whether the algorithm is probabilistic or deterministic. Next, we propose in the SSYNC model a probabilistic solution for the terminating exploration of torus-shaped networks of size âĂL, where 7â€ââ€L, by a team of 4 such weak robots. So, this algorithm is optimal w.r.t. the number of robots
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