2,429 research outputs found
Combining a hierarchical task network planner with a constraint satisfaction solver for assembly operations involving routing problems in a multi-robot context
This work addresses the combination of a symbolic hierarchical task network planner and a constraint satisfaction solver for the vehicle routing problem in a multi-robot context for structure assembly operations. Each planner has its own problem domain and search space, and the article describes how both planners interact in a loop sharing information in order to improve the cost of the solutions. The vehicle routing problem solver gives an initial assignment of parts to robots, making the distribution based on the distance among parts and robots, trying also to maximize the parallelism of the future assembly operations evaluating during the process the dependencies among the parts assigned to each robot. Then, the hierarchical task network planner computes a scheduling for the given assignment and estimates the cost in terms of time spent on the structure assembly. This cost value is then given back to the vehicle routing problem solver as feedback to compute a better assignment, closing the loop and repeating again the whole process. This interaction scheme has been tested with different constraint satisfaction solvers for the vehicle routing problem. The article presents simulation results in a scenario with a team of aerial robots assembling a structure, comparing the results obtained with different configurations of the vehicle routing problem solver and showing the suitability of using this approach.Unión Europea ARCAS FP7-ICT-287617Unión Europea H2020-ICT-644271Unión europea H2020-ICT-73166
Computational intelligence approaches to robotics, automation, and control [Volume guest editors]
No abstract available
NASA space station automation: AI-based technology review
Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures
Coordination control of robot manipulators using flat outputs
Published ArticleThis paper focuses on the synchronizing control of multiple interconnected flexible robotic manipulators
using differential flatness theory. The flatness theory has the advantage of simplifying trajectory tracking
tasks of complex mechanical systems. Using this theory, we propose a new synchronization scheme
whereby a formation of flatness based systems can be stabilized using their respective flat outputs.
Using the flat outputs, we eliminate the need for cross coupling laws and communication protocols
associated with such formations. The problem of robot coordination is reduced to synchronizing the
flat outputs between the respective robot manipulators. Furthermore, the selection of the flat output
used for the synchronizing control is not restricted as any system variable can be used. The problem of
unmeasured states used in the control is also solved by reconstructing the missing states using flatness
based interpolation. The proposed control law is less computationally intensive when compared to earlier
reported work as integration of the differential equations is not required. Simulations using a formation
of single link flexible joint robots are used to validate the proposed synchronizing control
Coordination control of robot manipulators using flat outputs
Published ArticleThis paper focuses on the synchronizing control of multiple interconnected flexible robotic manipulators
using differential flatness theory. The flatness theory has the advantage of simplifying trajectory tracking
tasks of complex mechanical systems. Using this theory, we propose a new synchronization scheme
whereby a formation of flatness based systems can be stabilized using their respective flat outputs.
Using the flat outputs, we eliminate the need for cross coupling laws and communication protocols
associated with such formations. The problem of robot coordination is reduced to synchronizing the
flat outputs between the respective robot manipulators. Furthermore, the selection of the flat output
used for the synchronizing control is not restricted as any system variable can be used. The problem of
unmeasured states used in the control is also solved by reconstructing the missing states using flatness
based interpolation. The proposed control law is less computationally intensive when compared to earlier
reported work as integration of the differential equations is not required. Simulations using a formation
of single link flexible joint robots are used to validate the proposed synchronizing control
Architecture for planning and execution of missions with fleets of unmanned vehicles
Esta tesis presenta contribuciones en el campo de la planificación automática y la
programación de tareas, la rama de la inteligencia artificial que se ocupa de la
realización de estrategias o secuencias de acciones típicamente para su ejecución por
parte de vehículos no tripulados, robots autónomos y/o agentes inteligentes. Cuando se
intenta alcanzar un objetivo determinado, la cooperación puede ser un aspecto clave. La
complejidad de algunas tareas requiere la cooperación entre varios agentes. Mas aún,
incluso si una tarea es lo suficientemente simple para ser llevada a cabo por un único
agente, puede usarse la cooperación para reducir el coste total de la misma. Para realizar
tareas complejas que requieren interacción física con el mundo real, los vehículos no
tripulados pueden ser usados como agentes. En los últimos años se han creado y utilizado
una gran diversidad de plataformas no tripuladas, principalmente vehículos que pueden
ser dirigidos sin un humano a bordo, tanto en misiones civiles como militares.
En esta tesis se aborda la aplicación de planificación simbólica de redes jerárquicas
de tareas (HTN planning, por sus siglas en inglés) en la resolución de problemas de
enrutamiento de vehículos (VRP, por sus siglas en inglés) [18], en dominios que implican
múltiples vehículos no tripulados de capacidades heterogéneas que deben cooperar para
alcanzar una serie de objetivos específicos.
La planificación con redes jerárquicas de tareas describe dominios utilizando una
descripción que descompone conjuntos de tareas en subconjuntos más pequeños de
subtareas gradualmente, hasta obtener tareas del más bajo nivel que no pueden ser
descompuestas y se consideran directamente ejecutables. Esta jerarquía es similar al modo
en que los humanos razonan sobre los problemas, descomponiéndolos en subproblemas
según el contexto, y por lo tanto suelen ser fáciles de comprender y diseñar.
Los problemas de enrutamiento de vehículos son una generalización del problema del
viajante (TSP, por sus siglas en inglés). La resolución del problema del viajante consiste
en encontrar la ruta más corta posible que permite visitar una lista de ciudades, partiendo
y acabando en la misma ciudad. Su generalización, el problema de enrutamiento de
vehículos, consiste en encontrar el conjunto de rutas de longitud mínima que permite
cubrir todas las ciudades con un determinado número de vehículos. Ambos problemas
cuentan con una fuerte componente combinatoria para su resolución, especialmente en el caso del VRP, por lo que su presencia en dominios que van a ser tratados con un planificador
HTN clásico supone un gran reto.
Para la aplicación de un planificador HTN en la resolución de problemas de enrutamiento
de vehículos desarrollamos dos métodos. En el primero de ellos presentamos un sistema
de optimización de soluciones basado en puntuaciones, que nos permite una nueva forma
de conexión entre un software especializado en la resolución del VRP con el planificador
HTN. Llamamos a este modo de conexión el método desacoplado, puesto que resolvemos
la componente combinatoria del problema de enrutamiento de vehículos mediante un
solucionador específico que se comunica con el planificador HTN y le suministra la
información necesaria para continuar con la descomposición de tareas. El segundo método
consiste en mejorar el planificador HTN utilizado para que sea capaz de resolver el
problema de enrutamiento de vehículos de la mejor forma posible sin tener que depender
de módulos de software externos. Llamamos a este modo el método acoplado. Con
este motivo hemos desarrollado un nuevo planificador HTN que utiliza un algoritmo de
búsqueda distinto del que se utiliza normalmente en planificadores de este tipo.
Esta tesis presenta nuevas contribuciones en el campo de la planificación con redes
jerárquicas de tareas para la resolución de problemas de enrutamiento de vehículos. Se
aplica una nueva forma de conexión entre dos planificadores independientes basada en
un sistema de cálculo de puntuaciones que les permite colaborar en la optimización de
soluciones, y se presenta un nuevo planificador HTN con un algoritmo de búsqueda distinto
al comúnmente utilizado. Se muestra la aplicación de estos dos métodos en misiones
civiles dentro del entorno de los Proyectos ARCAS y AEROARMS financiados por la
Comisión Europea y se presentan extensos resultados de simulación para comprobar la
validez de los dos métodos propuestos.This thesis presents contributions in the field of automated planning and scheduling,
the branch of artificial intelligence that concerns the realization of strategies or
action sequences typically for execution by unmanned vehicles, autonomous robots and/or
intelligent agents. When trying to achieve certain goal, cooperation may be a key aspect.
The complexity of some tasks requires the cooperation among several agents. Moreover,
even if the task is simple enough to be carried out by a single agent, cooperation can be
used to decrease the overall cost of the operation. To perform complex tasks that require
physical interaction with the real world, unmanned vehicles can be used as agents. In the
last years a great variety of unmanned platforms, mainly vehicles that can be driven without
a human on board, have been developed and used both in civil and military missions.
This thesis deals with the application of Hierarchical Task Network (HTN) planning
in the resolution of vehicle routing problems (VRP) [18] in domains involving multiple
heterogeneous unmanned vehicles that must cooperate to achieve specific goals.
HTN planning describes problem domains using a description that decomposes set of
tasks into subsets of smaller tasks and so on, obtaining low-level tasks that cannot be
further decomposed and are supposed to be executable. The hierarchy resembles the way
the humans reason about problems by decomposing them into sub-problems depending
on the context and therefore tend to be easy to understand and design.
Vehicle routing problems are a generalization of the travelling salesman problem (TSP).
The TSP consists on finding the shortest path that connects all the cities from a list, starting
and ending on the same city. The VRP consists on finding the set of minimal routes that
cover all cities by using a specific number of vehicles. Both problems have a combinatorial
nature, specially the VRP, that makes it very difficult to use a HTN planner in domains
where these problems are present.
Two approaches to use a HTN planner in domains involving the VRP have been tested.
The first approach consists on a score-based optimization system that allows us to apply a
new way of connecting a software specialized in the resolution of the VRP with the HTN
planner. We call this the decoupled approach, as we tackle the combinatorial nature of the
VRP by using a specialized solver that communicates with the HTN planner and provides
all the required information to do the task decomposition. The second approach consists on improving and enhancing the HTN planner to be capable of solving the VRP without
needing the use of an external software. We call this the coupled approach. For this reason,
a new HTN planner that uses a different search algorithm from these commonly used in
that type of planners has been developed and is presented in this work.
This thesis presents new contributions in the field of hierarchical task network planning
for the resolution of vehicle routing problem domains. A new way of connecting two
independent planning systems based on a score calculation system that lets them cooperate
in the optimization of the solutions is applied, and a new HTN planner that uses a different
search algorithm from that usually used in other HTN planners is presented. These two
methods are applied in civil missions in the framework of the ARCAS and AEROARMS
Projects funded by the European Commission. Extensive simulation results are presented
to test the validity of the two approaches
Study of robotics systems applications to the space station program
Applications of robotics systems to potential uses of the Space Station as an assembly facility, and secondarily as a servicing facility, are considered. A typical robotics system mission is described along with the pertinent application guidelines and Space Station environmental assumptions utilized in developing the robotic task scenarios. A functional description of a supervised dual-robot space structure construction system is given, and four key areas of robotic technology are defined, described, and assessed. Alternate technologies for implementing the more routine space technology support subsystems that will be required to support the Space Station robotic systems in assembly and servicing tasks are briefly discussed. The environmental conditions impacting on the robotic configuration design and operation are reviewed
Automated NDT inspection for large and complex geometries of composite materials
Large components with complex geometries, made of composite materials, have become very common in modern structures. To cope with future demand projections, it is necessary to overcome the current non-destructive testing (NDT) bottlenecks encountered during the inspection phase of manufacture. This thesis investigates several aspects of the introduction of automation within the inspection process of complex parts. The use of six-axis robots for product inspection and non-destructive testing systems is the central investigation of this thesis. The challenges embraced by the research include the development of a novel controlling approach for robotic manipulators and of novel path-planning strategies. The integration of robot manipulators and NDT data acquisition instruments is optimized. An effective and reliable way to encode the NDT data through the interpolated robot feedback positions is implemented. The viability of the new external control method is evaluated experimentally. The observed maximum position and orientation errors are respectively within 2mm and within 1 degree, over an operating envelope of 3m³. A new software toolbox (RoboNDT), aimed at NDT technicians, has been developed during this work. RoboNDT is intended to transform the robot path-planning problem into an easy step of the inspection process. The software incorporates the novel path-planning algorithms developed during this research and is shaped to overcome practical limitations of current OLP software. The software has been experimentally validated using scans on real high value aerospace components. RoboNDT delivers tool-path errors that are lower than the errors given by commercial off-line path-planning software. For example the variability of the standoff is within 10 mm for the tool-paths created with the commercial software and within 4.5 mm for the RoboNDT tool-paths, over a scanned area of 1.6m². The output of this research was used to support a 3-year industrial project, called IntACom and led by TWI on behalf of major aerospace sponsors. The result is a demonstrator system, currently in use at TWI Technology Centre, which is capable of inspecting complex geometries with high throughput. The IntACom system can scan real components 2.8 times faster than traditional 3-DoF scanners deploying phased-array inspection and 6.7 times faster than commercial gantry systems deploying traditional single-element inspection.Large components with complex geometries, made of composite materials, have become very common in modern structures. To cope with future demand projections, it is necessary to overcome the current non-destructive testing (NDT) bottlenecks encountered during the inspection phase of manufacture. This thesis investigates several aspects of the introduction of automation within the inspection process of complex parts. The use of six-axis robots for product inspection and non-destructive testing systems is the central investigation of this thesis. The challenges embraced by the research include the development of a novel controlling approach for robotic manipulators and of novel path-planning strategies. The integration of robot manipulators and NDT data acquisition instruments is optimized. An effective and reliable way to encode the NDT data through the interpolated robot feedback positions is implemented. The viability of the new external control method is evaluated experimentally. The observed maximum position and orientation errors are respectively within 2mm and within 1 degree, over an operating envelope of 3m³. A new software toolbox (RoboNDT), aimed at NDT technicians, has been developed during this work. RoboNDT is intended to transform the robot path-planning problem into an easy step of the inspection process. The software incorporates the novel path-planning algorithms developed during this research and is shaped to overcome practical limitations of current OLP software. The software has been experimentally validated using scans on real high value aerospace components. RoboNDT delivers tool-path errors that are lower than the errors given by commercial off-line path-planning software. For example the variability of the standoff is within 10 mm for the tool-paths created with the commercial software and within 4.5 mm for the RoboNDT tool-paths, over a scanned area of 1.6m². The output of this research was used to support a 3-year industrial project, called IntACom and led by TWI on behalf of major aerospace sponsors. The result is a demonstrator system, currently in use at TWI Technology Centre, which is capable of inspecting complex geometries with high throughput. The IntACom system can scan real components 2.8 times faster than traditional 3-DoF scanners deploying phased-array inspection and 6.7 times faster than commercial gantry systems deploying traditional single-element inspection
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