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Robust Indoor Localization Using Optimal Fusion Filter For Sensors And Map Layout Information
(2014)
Adapting plans to changes in the environment by finding alternatives and taking advantage of opportunities is a common human behavior. The need for such behavior is often rooted in the uncertainty produced by our incomplete knowledge of the environment. While several existing planning approaches deal with such issues, artificial agents still lack the robustness that humans display in accomplishing their tasks. In this work, we address this brittleness by combining Hierarchical Task Network planning, Description Logics, and the notions of affordances and conceptual similarity. The approach allows a domestic service robot to find ways to get a job done by making substitutions. We show how knowledge is modeled, how the reasoning process is used to create a constrained planning problem, and how the system handles cases where plan generation fails due to missing/unavailable objects. The results of the evaluation for two tasks in a domestic service domain show the viability of the approach in finding and making the appropriate goal transformations.
Level-Synchronous Parallel Breadth-First Search Algorithms For Multicore and Multiprocessor Systems
(2014)
Breadth-First Search (BFS) is a graph traversal technique used in many applications as a building block, e.g.,~to systematically explore a search space. For modern multicore processors and as application graphs get larger, well-performing parallel algorithms are favourable. In this paper, we systematically evaluate an important class of parallel BFS algorithms and discuss programming optimization techniques for their implementation. We concentrate our discussion on level-synchronous algorithms for larger multicore and multiprocessor systems. In our results, we show that for small core counts many of these algorithms show rather similar behaviour. But, for large core counts and large graphs, there are considerable differences in performance and scalability influenced by several factors. This paper gives advice, which algorithm should be used under which circumstances.
Residential and commercial buildings are responsible for about 40% of the EU’s total energy consumption. However, conscious, sustainable use of this limited resource is hampered by a lack of visibility and materiality of consumption. One of the major challenges is enabling consumers to make informed decisions about energy consumption, thereby supporting the shift to sustainable actions. With the use of Energy-Management-Systems it is possible to save up to 15%. In recent years, design approaches have greatly diversified, but with the emergence of ubiquitous- and context-aware computing, energy feedback solutions can be enriched with additional context information. In this study, we present the concept “room as a context” for eco-feedback systems. We investigate opportunities of making current state-of-the-art energy visualizations more meaningful and demonstrate which new forms of visualizations can be created with this additional information. Furthermore, we developed a prototype for android-based tablets, which includes some of the presented features to study our design concepts in the wild.
The RoCKIn@Work Challenge
(2014)
In general, mathematics plays a central role in our lives because today mathematics regulates our everyday life with techniques, technologies and procedures, for example coding techniques for credit cards or the drafting of curves and surfaces for construction procedures [5]. Obviously, mathematics continues to be an important element of engineering education and it still represents a major obstacle for the students. Lacking the knowledge of several topics, changing learning behavior and inadequate overall conditions at universities for the repetition of school mathematics were mentioned to be causes for the constantly increasing gap between the initial level of mathematics at university and the prior knowledge of the first semester students [2].
SOA-Readiness of REST
(2014)