5,204 research outputs found

    β\beta-Stars or On Extending a Drawing of a Connected Subgraph

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    We consider the problem of extending the drawing of a subgraph of a given plane graph to a drawing of the entire graph using straight-line and polyline edges. We define the notion of star complexity of a polygon and show that a drawing ΓH\Gamma_H of an induced connected subgraph HH can be extended with at most min{h/2,β+log2(h)+1}\min\{ h/2, \beta + \log_2(h) + 1\} bends per edge, where β\beta is the largest star complexity of a face of ΓH\Gamma_H and hh is the size of the largest face of HH. This result significantly improves the previously known upper bound of 72V(H)72|V(H)| [5] for the case where HH is connected. We also show that our bound is worst case optimal up to a small additive constant. Additionally, we provide an indication of complexity of the problem of testing whether a star-shaped inner face can be extended to a straight-line drawing of the graph; this is in contrast to the fact that the same problem is solvable in linear time for the case of star-shaped outer face [9] and convex inner face [13].Comment: Appears in the Proceedings of the 26th International Symposium on Graph Drawing and Network Visualization (GD 2018

    A New Approach to Time-Optimal Path Parameterization based on Reachability Analysis

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    Time-Optimal Path Parameterization (TOPP) is a well-studied problem in robotics and has a wide range of applications. There are two main families of methods to address TOPP: Numerical Integration (NI) and Convex Optimization (CO). NI-based methods are fast but difficult to implement and suffer from robustness issues, while CO-based approaches are more robust but at the same time significantly slower. Here we propose a new approach to TOPP based on Reachability Analysis (RA). The key insight is to recursively compute reachable and controllable sets at discretized positions on the path by solving small Linear Programs (LPs). The resulting algorithm is faster than NI-based methods and as robust as CO-based ones (100% success rate), as confirmed by extensive numerical evaluations. Moreover, the proposed approach offers unique additional benefits: Admissible Velocity Propagation and robustness to parametric uncertainty can be derived from it in a simple and natural way.Comment: 15 pages, 9 figure
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