Model-Based Recognition and Localization From Sparse Range or Tactile Data 1983


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    • Author:  by A. I. Meno  Tom?s Lozano-P?rez  Model:based Recognit Ion  W. Eric  W. Eric L. Grimson  Torns Lozano-prez  

    • Abstract:  This paper discusses how local measurements of three-dimensional pool[ions and surface normals (recorded by a set of tactile sensors, or by threedimensional range sensors), may be used o identify and locate objects, from among a set, of known objects. The objects are modeled as po!yhedra having up to six degrees of freedom relative to the sensors. We show tiat inconsistent, hypotheses about pairings between sensed points and object, surfaces can be discarded efficiently by using local constraints on: distoances bet,ween faces, angles betwee, face normals, and angles (reiatAve to t. he surface normals) of vectors between sensed points. We show by simulation and by mathematical bounds that the number of hypotheses consisten; with these constraints is small. We also show how to recover the position and orient, at, ion of the object from the sense daiwa. The algorithm's performance on data obt,ained from a triangulation range sensor is illustrated.

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