A Hierarchical Extension of the D ∗ Algorithm

In this paper a contribution to the practice of path planning using a new hierarchical extension of the D ∗ algorithm is introduced. A hierarchical graph is stratified into several abstraction levels and used to model environments for path planning. The hierarchical D∗ algorithm uses a downtop strategy and a set of pre-calculated trajectories in order to improve performance. This allows optimality and specially lower computational time. It is experimentally proved how hierarchical search algorithms and on-line path planning algorithms based on topological abstractions can be combined successfully

Hierarchical Path Search with Partial Materialization of Costs for a Smart Wheelchair

In this paper, the off-line path planner module of a smart wheelchair aided navigation system is described. Environmental information is structured into a hierarchical graph (H-graph) and used either by the user interface or the path planner module. This information structure facilitates efficient path search and easier information access and retrieval. Special path planning issues like planning between floors of a building (vertical path planning) are also viewed. The H-graph proposed is modelled by a tree. The hierarchy of abstractions contained in the tree has several levels of detail. Each abstraction level is a graph whose nodes can represent other graphs in a deeper level of the hierarchy. Path planning is performed using a path skeleton which is built from the deepest abstraction levels of the hierarchy to the most upper levels and completed in the last step of the algorithm. In order not to lose accuracy in the path skeleton generation and speed up the search, a set of optimal subpaths are previously stored in some nodes of the H-graph (path costs are partially materialized). Finally, some experimental results are showed and compared to traditional heuristic search algorithms used in robot path planning.Comisión Interministerial de Ciencia y Tecnología TER96-2056-C02-0

Hierarchical D ∗ algorithm with materialization of costs for robot path planning

In this paper a new hierarchical extension of the D ∗ algorithm for robot path planning is introduced. The hierarchical D ∗ algorithm uses a down-top strategy and a set of precalculated paths (materialization of path costs) in order to improve performance. This on-line path planning algorithm allows optimality and specially lower computational time. H-Graphs (hierarchical graphs) are modified and adapted to support on-line path planning with materialization of costs and multiple hierarchical levels. Traditional on-line robot path planning focused in horizontal spaces is also extended to vertical and interbuilding spaces. Some experimental results are showed and compared to other path planning algorithms

A multiple layer model to compare RNA secondary structures

International audienceWe formally introduce a new data structure, called MiGaL for ``Multiple Graph Layers'', that is composed of various graphs linked together by relations of abstraction/refinement. The new structure is useful for representing information that can be described at different levels of abstraction, each level corresponding to a graph. We then propose an algorithm for comparing two MiGaLs. The algorithm performs a step-by-step comparison starting with the most ``abstract'' level. The result of the comparison at a given step is communicated to the next step using a special colouring scheme. MiGaLs represent a very natural model for comparing RNA secondary structures that may be seen at different levels of detail, going from the sequence of nucleotides, single or paired with another to participate in a helix, to the network of multiple loops that is believed to represent the most conserved part of RNAs having similar function. We therefore show how to use MiGaLs to very efficiently compare two RNAs of any size at different levels of detail

Umgebungsmodelle und Navigationsdaten für ortsbezogene Dienste in Gebäuden

Ortsbezogene Dienste in Gebäuden (Indoor Location-based Services, I-LBS) sammeln, verarbeiten und stellen Informationen bereit, die in Abhängigkeit der Aufenthaltsorte ihrer Zielobjekte sowie auf der Grundlage eines Umgebungsmodells des jeweiligen Gebäudes berechnet werden. Die Anwendungsbereiche von I-LBS reichen dabei von personenbezogenen Diensten wie z.B. Navigation, ortsbezogenen Benachrichtigungen und Ressourcen-Suche über organisationsbezogene Dienste zur Steuerung und Optimierung von Arbeitsprozessen und Ressourcen bis hin zu Anwendungen, die personen- und organisationsübergreifend Informationen über Zielobjekte und deren jeweilige Umgebungen austauschen. Für die Erzeugung und Nutzung von Umgebungsmodellen ergeben sich mehrere Herausforderungen: Bei der automatischen Erzeugung eines Modells müssen die Eigenschaften eines Gebäudes so erfasst werden, dass dadurch nicht nur Orte gesucht oder kürzeste Wege ermittelt werden können, sondern auch Navigationsdaten für die Berechnung von Navigationsanweisungen zur Verfügung stehen. Dabei stellt sich die Frage, wie ein solches Umgebungsmodell aufgebaut sein muss und wie es sich berechnen lässt. Zur Bereitstellung für verschiedene Dienste wird ein geeignetes Format benötigt, in dem alle relevanten geometrischen, symbolischen und topologischen Informationen über ein Gebäude abgebildet sind. Eine wichtige Rolle spielen dabei auch unterschiedliche Positionierungsverfahren, die miteinander kombiniert werden können und deren heterogene Positionsdaten integriert werden müssen. Für die Realisierung von Indoor-Navigationssystemen besteht sowohl bei stationären als auch bei mobilen Lösungen eine Herausforderung in der Berechnung von dedizierten Navigationsanweisungen. Diese leiten einen Benutzer anhand von textbasierten oder graphischen Hinweisen zu seinem Ziel, dabei können auch Landmarken in die Navigationsanweisungen mit einbezogen werden. Im Rahmen dieser Dissertation werden neue Lösungen für die vorgenannten Probleme aufgezeigt, und die entwickelten Konzepte werden anhand von Simulationen sowie praktischen Umsetzungen diskutiert.Indoor Location-based Services (I-LBS) collect, process and provide information by taking into account the properties of a building and the locations of mobile targets inside. Application scenarios for I-LBS include personal services such as navigation, location-dependent notifications or searching for resources, as well as corporate services for managing and optimizing workflows, and services that combine location data from targets among several organizations. Creating and utilizing a location model involves several challenges: the properties of a building need to be modeled in a way which allows for computations not limited to searching for nearby places or calculating shortest paths, but also include navigation data, which is required for providing navigation instructions. Thus a central question is which information should be included in a location model and how can it be computed. In order to provide location models for different services, an appropriate format is required, which covers the relevant geometric, symbolic and topological information. Also positioning systems play an important part, given that they can be combined with each other and that their heterogeneous position data need to be integrated. Providing intelligible and dedicated navigation instructions poses a challenge for the realization of both stationary and mobile indoor navigation systems. Such instructions guide users to their destination by means of textual or graphical references, which both can be further enriched by incorporating landmarks into the navigation instructions. This dissertation develops new solutions to the above-mentioned problems and the presented concepts are evaluated on the basis of simulations and practical implementations