By Topic

A new algorithm for computing minimum distance

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sundaraj, K. ; INRIA Rhone-Alpes, Montbonnot Saint Martin, France ; D'Aulignac, D. ; Mazer, E.

This paper presents a new algorithm for computing the minimum distance between convex polyhedras. The algorithm of Gilbert-Johnson-Keerthi (GJK) and the algorithm of Lin-Canny (LC) are well-known fast solutions to the problem. We show how a mix between LC's idea and the GJK's algorithm can be used to solve the problem. In our algorithm, we use local methods to calculate the distance between features and new “updating” conditions to add stability. These new conditions enable one to ensure more stability when compared to GJK. We also modify our terminating conditions to add robustness to our approach. Our experiments also show that the expected running time of our approach is constant, independent of the complexity of the polyhedra. We present some comparisons of our method with GJK

Published in:

Intelligent Robots and Systems, 2000. (IROS 2000). Proceedings. 2000 IEEE/RSJ International Conference on  (Volume:3 )

Date of Conference:

2000