25,319 research outputs found

    CDDT: Fast Approximate 2D Ray Casting for Accelerated Localization

    Full text link
    Localization is an essential component for autonomous robots. A well-established localization approach combines ray casting with a particle filter, leading to a computationally expensive algorithm that is difficult to run on resource-constrained mobile robots. We present a novel data structure called the Compressed Directional Distance Transform for accelerating ray casting in two dimensional occupancy grid maps. Our approach allows online map updates, and near constant time ray casting performance for a fixed size map, in contrast with other methods which exhibit poor worst case performance. Our experimental results show that the proposed algorithm approximates the performance characteristics of reading from a three dimensional lookup table of ray cast solutions while requiring two orders of magnitude less memory and precomputation. This results in a particle filter algorithm which can maintain 2500 particles with 61 ray casts per particle at 40Hz, using a single CPU thread onboard a mobile robot.Comment: 8 pages, 14 figures, ICRA versio

    Real-Time, Three-Dimensional Object Detection and Modeling in Construction

    Get PDF

    Through a glass darkly: a case for the study of virtual space

    Get PDF
    This paper begins to examine the similarities and differences between virtual space and real space, as taken from anarchitectural (as opposed to a biological, psychological, geographic, philosophical or information theoretic)standpoint. It continues by introducing a number of criteria, suggested by the authors as being necessary for virtualspace to be used in a manner consistent with our experience of real space. Finally, it concludes by suggesting apedagogical framework for the benefits and associated learning outcomes of the study and examination of thisrelationship. This is accompanied by examples of recent student work, which set out to investigate this relationship

    Through a glass darkly: a case for the study of virtual space

    Get PDF
    This paper begins to examine the similarities and differences between virtual space and real space, as taken from anarchitectural (as opposed to a biological, psychological, geographic, philosophical or information theoretic)standpoint. It continues by introducing a number of criteria, suggested by the authors as being necessary for virtualspace to be used in a manner consistent with our experience of real space. Finally, it concludes by suggesting apedagogical framework for the benefits and associated learning outcomes of the study and examination of thisrelationship. This is accompanied by examples of recent student work, which set out to investigate this relationship

    Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps

    Full text link
    Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks a robot can accomplish and makes it harder to deal with uncertainties that are present in the context of real-time robotics applications. In this work, we present Topomap, a framework which simplifies the navigation task by providing a map to the robot which is tailored for path planning use. This novel approach transforms a sparse feature-based map from a visual Simultaneous Localization And Mapping (SLAM) system into a three-dimensional topological map. This is done in two steps. First, we extract occupancy information directly from the noisy sparse point cloud. Then, we create a set of convex free-space clusters, which are the vertices of the topological map. We show that this representation improves the efficiency of global planning, and we provide a complete derivation of our algorithm. Planning experiments on real world datasets demonstrate that we achieve similar performance as RRT* with significantly lower computation times and storage requirements. Finally, we test our algorithm on a mobile robotic platform to prove its advantages.Comment: 8 page
    corecore