DocumentCode
1759956
Title
Efficient Proximity Probing Algorithms for Metrology
Author
Adler, Aviv ; Panahi, Fatemeh ; van der Stappen, A. Frank ; Goldberg, K.
Author_Institution
Dept. of Math., Princeton Univ., Princeton, NJ, USA
Volume
12
Issue
1
fYear
2015
fDate
Jan. 2015
Firstpage
84
Lastpage
95
Abstract
Metrology, the theoretical and practical study of measurement, has applications in automated manufacturing, inspection, robotics, surveying, and healthcare. The geometric probing problem considers how to optimally use a probe to measure geometric properties. In this paper, we consider a proximity probe which, given a point, returns the distance to the boundary of the nearest object. When there is an unknown convex polygon P in the plane, the goal is to minimize the number of probe measurement needed to exactly determine the shape and location of P. We present an algorithm with upper bound of 3.5n + k + 2 probes, where n is the number of vertices and k ≤ 3 is the number of acute angles of P. The algorithm requires constant time per probe, and hence, O(n) time to determine P. We also address the related problem where the unknown polygon is a member of a known finite set Γ and the goal is to efficiently determine which polygon is present. When m is the size of Γ and n´ is the maximum number of vertices of any member of Γ, we present an algorithm with an upper bound of 2n + 2 probes with O(1) computations per probe and a O(n´m) preprocessing phase (depending only on Γ).
Keywords
measurement theory; set theory; O(n´m) preprocessing phase; automated manufacturing; convex polygon; finite set; geometric probing problem; geometric property measurement; healthcare; inspection; metrology; probe measurement; proximity probing algorithm; robotics; surveying; upper bound; Algorithm design and analysis; Clocks; Metrology; Probes; Robot sensing systems; Shape; Shape measurement; Computational geometry; metrology; probes;
fLanguage
English
Journal_Title
Automation Science and Engineering, IEEE Transactions on
Publisher
ieee
ISSN
1545-5955
Type
jour
DOI
10.1109/TASE.2014.2357763
Filename
6915767
Link To Document