34 research outputs found
Between Subgraph Isomorphism and Maximum Common Subgraph
When a small pattern graph does not occur inside a larger target graph, we can ask how to find "as much of the pattern as possible" inside the target graph. In general, this is known as the maximum common subgraph problem, which is much more computationally challenging in practice than subgraph isomorphism. We introduce a restricted alternative, where we ask if all but k vertices from the pattern can be found in the target graph. This allows for the development of slightly weakened forms of certain invariants from subgraph isomorphism which are based upon degree and number of paths. We show that when k is small, weakening the invariants still retains much of their effectiveness. We are then able to solve this problem on the standard problem instances used to benchmark subgraph isomorphism algorithms, despite these instances being too large for current maximum common subgraph algorithms to handle. Finally, by iteratively increasing k, we obtain an algorithm which is also competitive for the maximum common subgraph
Hybrid mapping for static and non-static indoor environments
Menci贸n Internacional en el t铆tulo de doctorIndoor environments populated by humans, such as houses, offices or universities,
involve a great complexity due to the diversity of geometries and situations that they
may present. Apart from the size of the environment, they can contain multiple rooms
distributed into floors and corridors, repetitive structures and loops, and they can
get as complicated as one can imagine. In addition, the structure and situations that
the environment present may vary over time as objects could be moved, doors can
be frequently opened or closed and places can be used for different purposes. Mobile
robots need to solve these challenging situations in order to successfully operate in
the environment. The main tools that a mobile robot has for dealing with these
situations relate to navigation and perception and comprise mapping, localization,
path planning and map adaptation. In this thesis, we try to address some of the open
problems in robot navigation in non-static indoor environments. We focus on house-like
environments as the work is framed into the HEROITEA research project that aims
attention at helping elderly people with their everyday-life activities at their homes.
This thesis contributes to HEROITEA with a complete robotic mapping system and
map adaptation that grants safe navigation and understanding of the environment.
Moreover, we provide localization and path planning strategies within the resulting
map to further operate in the environment.
The first problem tackled in this thesis is robot mapping in static indoor environments.
We propose a hybrid mapping method that structures the information gathered
from the environment into several maps. The hybrid map contains diverse knowledge of
the environment such as its structure, the navigable and blocked paths, and semantic
knowledge, such as the objects or scenes in the environment. All this information is
separated into different components of the hybrid map that are interconnected so the
system can, at any time, benefit from the information contained in every component.
In addition to the conceptual conception of the hybrid map, we have also developed
building procedures and an exploration algorithm to autonomous build the hybrid
map.
However, indoor environments populated by humans are far from being static as
the environment may change over time. For this reason, the second problem tackled in
this thesis is the adaptation of the map to non-static environments. We propose an
object-based probabilistic map adaptation that calculates the likelihood of moving or
remaining in its place for the different objects in the environment.
Finally, a map is just a description of the environment whose importance is mostly
related to how the map is used. In addition, map representations are more valuable
as long as they offer a wider range of applications. Therefore, the third problem
that we approach in this thesis is exploiting the intrinsic characteristics of the hybrid
map in order to enhance the performance of localization and path planning methods.
The particular objectives of these approaches are precision for robot localization and
efficiency for path planning in terms of execution time and traveled distance.
We evaluate our proposed methods in a diversity of simulated and real-world indoor
environments. In this extensive evaluation, we show that hybrid maps can be efficiently
built and maintained over time and they open up for new possibilities for localization
and path planning. In this thesis, we show an increase in localization precision and
robustness and an improvement in path planning performance.
In sum, this thesis makes several contributions in the context of robot navigation
in indoor environments, and especially in hybrid mapping. Hybrid maps offer higher
efficiency during map building and other applications such as localization and path
planning. In addition, we highlight the necessity of dealing with the dynamics of
indoor environments and the benefits of combining topological, semantic and metric
information to the autonomy of a mobile robot.Los entornos de interiores habitados por personas, como casas, oficinas o universidades,
entra帽an una gran complejidad por la diversidad de geometr铆as y situaciones que pueden
ocurrir. Aparte de las diferencias en tama帽o, estos entornos pueden contener muchas
habitaciones organizadas en diferentes plantas o pasillos, pueden presentar estructuras
repetitivas o bucles de tal forma que los entornos pueden llegar a ser tan complejos como
uno se pueda imaginar. Adem谩s, la estructura y el estado del entorno pueden variar
con el tiempo, ya que los objetos pueden moverse, las puertas pueden estar cerradas o
abiertas y diferentes espacios pueden ser usados para diferentes prop贸sitos. Los robots
m贸viles necesitan resolver estas situaciones dif铆ciles para poder funcionar de una forma
satisfactoria. Las principales herramientas que tiene un robot m贸vil para manejar
estas situaciones est谩n relacionadas con la navegaci贸n y la percepci贸n y comprenden el
mapeado, la localizaci贸n, la planificaci贸n de trayectorias y la adaptaci贸n del mapa. En
esta tesis, abordamos algunos de los problemas sin resolver de la navegaci贸n de robots
m贸viles en entornos de interiores no est谩ticos. Nos centramos en entornos tipo casa ya
que este trabajo se enmarca en el proyecto de investigaci贸n HEROITEA que se enfoca
en ayudar a personas ancianas en tareas cotidianas del hogar. Esta tesis contribuye al
proyecto HEROITEA con un sistema completo de mapeado y adaptaci贸n del mapa
que asegura una navegaci贸n segura y la comprensi贸n del entorno. Adem谩s, aportamos
m茅todos de localizaci贸n y planificaci贸n de trayectorias usando el mapa construido para
realizar nuevas tareas en el entorno.
El primer problema que se aborda en esta tesis es el mapeado de entornos de
interiores est谩ticos por parte de un robot. Proponemos un m茅todo de mapeado h铆brido
que estructura la informaci贸n capturada en varios mapas. El mapa h铆brido contiene
informaci贸n sobre la estructura del entorno, las trayectorias libres y bloqueadas y
tambi茅n incluye informaci贸n sem谩ntica, como los objetos y escenas en el entorno. Toda
esta informaci贸n est谩 separada en diferentes componentes del mapa h铆brido que est谩n
interconectados de tal forma que el sistema puede beneficiarse en cualquier momento
de la informaci贸n contenida en cada componente. Adem谩s de la definici贸n conceptual del mapa h铆brido, hemos desarrollado unos procedimientos para construir el mapa y un
algoritmo de exploraci贸n que permite que esta construcci贸n se realice aut贸nomamente.
Sin embargo, los entornos de interiores habitados por personas est谩n lejos de ser
est谩ticos ya que pueden cambiar a lo largo del tiempo. Por esta raz贸n, el segundo
problema que intentamos solucionar en esta tesis es la adaptaci贸n del mapa para
entornos no est谩ticos. Proponemos un m茅todo probabil铆stico de adaptaci贸n del mapa
basado en objetos que calcula la probabilidad de que cada objeto en el entorno haya
sido movido o permanezca en su posici贸n anterior.
Para terminar, un mapa es simplemente una descripci贸n del entorno cuya importancia
est谩 principalmente relacionada con su uso. Por ello, los mapas m谩s valiosos
ser谩n los que ofrezcan un rango mayor de aplicaciones. Para abordar este asunto, el
tercer problema que intentamos solucionar es explotar las caracter铆sticas intr铆nsecas del
mapa h铆brido para mejorar el desempe帽o de m茅todos de localizaci贸n y de planificaci贸n
de trayectorias usando el mapa h铆brido. El objetivo principal de estos m茅todos es
aumentar la precisi贸n en la localizaci贸n del robot y la eficiencia en la planificaci贸n de
trayectorias en relaci贸n al tiempo de ejecuci贸n y la distancia recorrida.
Hemos evaluado los m茅todos propuestos en una variedad de entornos de interiores
simulados y reales. En esta extensa evaluaci贸n, mostramos que los mapas h铆bridos
pueden construirse y mantenerse en el tiempo de forma eficiente y que dan lugar a
nuevas posibilidades en cuanto a localizaci贸n y planificaci贸n de trayectorias. En esta
tesis, mostramos un aumento en la precisi贸n y robustez en la localizaci贸n y una mejora
en el desempe帽o de la planificaci贸n de trayectorias.
En resumen, esta tesis lleva a cabo diversas contribuciones en el 谩mbito de la
navegaci贸n de robots m贸viles en entornos de interiores, y especialmente en mapeado
h铆brido. Los mapas h铆bridos ofrecen m谩s eficiencia durante la construcci贸n del mapa
y en otras tareas como la localizaci贸n y la planificaci贸n de trayectorias. Adem谩s,
resaltamos la necesidad de tratar los cambios en entornos de interiores y los beneficios
de combinar informaci贸n topol贸gica, sem谩ntica y m茅trica para la autonom铆a del robot.Programa de Doctorado en Ingenier铆a El茅ctrica, Electr贸nica y Autom谩tica por la Universidad Carlos III de MadridPresidente: Carlos Balaguer Bernaldo de Quir贸s.- Secretario: Javier Gonz谩lez Jim茅nez.- Vocal: Nancy Marie Amat
Experimental Evaluation of Subgraph Isomorphism Solvers
International audienceSubgraph Isomorphism (SI) is an NP-complete problem which is at the heart of many structural pattern recognition tasks as it involves finding a copy of a pattern graph into a target graph. In the pattern recognition community, the most well-known SI solvers are VF2, VF3, and RI. SI is also widely studied in the constraint programming community, and many constraint-based SI solvers have been proposed since Ullman, such as LAD and Glasgow, for example. All these SI solvers can solve very quickly some large SI instances, that involve graphs with thousands of nodes. However, McCreesh et al. have recently shown how to randomly generate SI instances the hardness of which can be controlled and predicted, and they have built small instances which are computationally challenging for all solvers. They have also shown that some small instances, which are predicted to be easy and are easily solved by constraint-based solvers, appear to be challenging for VF2 and VF3. In this paper, we widen this study by considering a large test suite coming from eight benchmarks. We show that, as expected for an NP-complete problem, the solving time of an instance does not depend on its size, and that some small instances coming from real applications are not solved by any of the considered solvers. We also show that, if RI and VF3 can solve very quickly a large number of easy instances, for which Glasgow or LAD need more time, they fail at solving some other instances that are quickly solved by Glasgow or LAD, and they are clearly outperformed by Glasgow on hard instances. Finally, we show that we can easily combine solvers to take benefit of their complementarity
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Spatial arrangements in architecture and mechanical engineering: some aspects of their representation and construction
Spatial arrangements in architecture and mechanical engineering are represented by incidence structures and classified according to properties of these incidence structures. The relationships between classes are given by ornamentation operations and the construction of elements in fundamental classes by substructure replacement operations. Thus representations of the spatial arrangements for possible designs are generated.
Planar maps represent spatial arrangements in architecutral plans. The edges correspond to walls and vertices to incidence between walls. Plans represented by 3-vertex connected maps are ornamented by rooting and extension operations. Further ornamentation specifies access between regions. Plans with all regions adjacent to the exterior correspond to outerplane maps. Trivalent maps represent an important class of plans. Fundamental plans with r internal regions and s regions adjacent to the exterior are represented by [r,s] triangulations. Ornamentations of simple [r,s] triangulations are specified which represent plans with rectangular regions. Plans with walls aligned along two directions are represented by rectangular shapes whose maximal lines correspond to contiguous aligned walls. Rules of construction for various classes are given and the incidence structures of maximal lines and regions are characterized.
Spatial arrangements in machines are represented by systems whose blocks correspond to links and vertices to joints. The dual systems are also used. Coplanar kinematic chains with revolute pairs are classified according to mobility and connectedness. Two fundamental classes are considered. First, the chains with binary joints, represented by simple graphs and constructed by two new methods: (i) suspended chain and cycle addition and (ii) subgraph replacement. Second, the chains with binary links which are constructed by subgraph replacement
Constraints for symmetry breaking in graph representation
Many complex combinatorial problems arising from a range of scientific
applications (such as computer networks, mathematical chemistry and
bioinformatics) involve searching for an undirected graph satisfying a given
property. Since for any possible solution there can be a large number of isomorphic
representations, these problems can quickly become intractable. One
way to mitigate this problem is to eliminate as many isomorphic copies as
possible by breaking symmetry during search - i.e. by introducing constraints
that ensure that at least one representative graph is generated for each equivalence class, but not the entire class. The goal is to generate as few members
of each class as possible - ideally exactly one: the symmetry break is said
to be complete in this case. In this paper we introduce novel, effective and
compact, symmetry breaking constraints for undirected graph search. While
incomplete, these prove highly beneficial in pruning the search for a graph.
We illustrate the application of symmetry breaking in graph representation to
resolve several open instances in extremal graph theory. We also illustrate the application of our approach to graph edge coloring problems which exhibit additional
symmetries due to the fact that the colors of the edges in any solution
can be permuted
A Parallel, Backjumping Subgraph Isomorphism Algorithm Using Supplemental Graphs
This registry entry contains a reference to the code, data and experimental scripts needed to reproduce the subgraph isomorphism paper:
Ciaran McCreesh and Patrick Prosser, "A Parallel, Backjumping Subgraph Isomorphism Algorithm using Supplemental Graphs". To appear at the 21st International Conference on Principles and Practice of Constraint Programming (CP 2015)