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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.
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].
The perceived direction of “up” is determined by gravity, visual information, and an internal estimate of body orientation (Mittelstaedt, 1983; Dyde et al., 2006). Is the gravity level found on other worlds sufficient to maintain gravity’s contribution to this perception? Difficulties in stability reported anecdotally by astronauts on the lunar surface (NASA 1972) suggest that the moon’s gravity may not be, despite this value being far above the threshold for detecting linear acceleration. Knowing how much gravity is needed to provide a reliable orientation cue is required for training and preparing astronauts for future missions to the moon, mars and beyond.
Perception is one of the most important cognitive capabilities of an entity since it determines how an entity perceives its environment. The presented work focuses on providing cost efficient but realistic perceptual processes for intelligent virtual agents (IVAs) or NPCs with the goal of providing a sound information basis for the entities' decision making processes. In addition, an agent-central perception process should rovide a common interface for developers to retrieve data from the IVAs' environment. The overall process is evaluated by applying it to a scenario demonstrating its benefits. The evaluation indicates, that such a realistically simulated perception process provides a powerful instrument to enhance the (perceived) realism of an IVA's simulated behavior.
The work being described in this paper is the result of a cooperation project between the Institute of Visual Computing at the Bonn-Rhein-Sieg University of Applied Sciences, Germany and the Laboratory of Biomedical Engineering at the Federal University of Uberlândia, Brazil. The aim of the project is the development of a virtual environment based training simulator which enables for better and faster learning the control of upper limb prostheses. The focus of the paper is the description of the technical setup since learning tutorials still need to be developed as well as a comprehensive evaluation still needs to be carried out.