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Autonomous mobile robot global motion planning and geometric beacon collection using traversability vectors

IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION 1997年第1期13卷 132-140页

作者： Janet, JA Luo, RC Kay, MG Center for Robotics and Intelligent Machines Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA

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.

关键词： computational geometry collision detection geometric beacon detection/collection mobile robot motion planning range sensor prediction self-localization

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