Autonomous mobile robot global motion planning and geometric beacon collection using traversability vectors
Autonomous mobile robot global motion planning and geometric beacon collection using traversability vectors
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DOI：
10.1109/70.554354
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发表时间：
1997-02
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影响因子：
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通讯作者：
J. Janét;R. Luo;M. Kay
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文献类型：
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作者：
J. Janét;R. Luo;M. Kay
在全球运动规划（GMP）和几何信标收集（自定位）使用遍历向量的方法已经开发和实施的计算机仿真和实际实验移动的机器人。这两种方法都基于相同的简单，模块化和多功能的可遍历向量（t向量）。通过实施，已经发现，t-向量减少了检测路径障碍物、欧几里德最优经由点和几何信标以及识别传感器可见的特征的计算要求。环境可以是静态的或动态的，并且允许多边形重叠（即，相交或嵌套）。虽然t向量模型确实要求多边形是凸的，但将凹多边形分解为凸多边形集比要求多边形不重叠要简单得多，这是许多其他GMP模型所要求的。T向量还减少了标准V图及其变体的数据大小和复杂性。本文提出了t向量模型，以便读者可以将其应用于移动的机器人GMP和自定位。
Approaches in global motion planning (GMP) and geometric beacon collection (for self-localization) using traversability vectors have been developed and implemented in both computer simulation and actual experiments on mobile robots. Both approaches are based on the same simple, modular, and multifunctional traversability vector (t-vector). Through implementation it has been found that t-vectors reduce the computational requirements to detect path obstructions, Euclidean optimal via-points, and geometric beacons, as well as to identify which features are visible to sensors. Environments can be static or dynamic and polygons are permitted to overlap (i.e., intersect or be nested). While the t-vector model does require that polygons be convex, it is a much simpler matter to decompose concave polygons into convex polygon sets than it is to require that polygons not overlap, which is required for many other GMP models. T-vectors also reduce the data size and complexity of standard V-graphs and variations thereof. This paper presents the t-vector model so that the reader can apply it to mobile robot GMP and self-localization.