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Accurate evaluation of a distance function for optimization-based motion planning

Title
Accurate evaluation of a distance function for optimization-based motion planning
Authors
Lee Y.Lengagne S.Kheddar A.Kim Y.J.
Ewha Authors
김영준
SCOPUS Author ID
김영준scopus
Issue Date
2012
Journal Title
IEEE International Conference on Intelligent Robots and Systems
ISSN
2153-0858JCR Link
Citation
pp. 1513 - 1518
Indexed
SCOPUS scopus
Abstract
We propose three novel methods to evaluate a distance function for robotic motion planning based on semiinfinite programming (SIP) framework; these methods include golden section search (GSS), conservative advancement (CA) and a hybrid of GSS and CA. The distance function can have a positive and a negative value, each of which corresponds to the Euclidean distance and penetration depth, respectively. In our approach, each robot's link is approximated and bounded by a capsule shape, and the distance between some selected link pairs is continuously evaluated along the joint's trajectory, provided by the SIP solver, and the global minimum distance is found. This distance is fed into the SIP solver, which subsequently suggests a new trajectory. This process is iterated until no negative distance is found anywhere in the links of the robot.We have implemented the three distance evaluation methods, and experimentally validated that the proposed methods effectively and accurately find the global minimum distances to generate a self-collision-free motion for the HRP-2 humanoid robot. Moreover, we demonstrate that the hybrid method outperforms other two methods in terms of computational speed and reliability. © 2012 IEEE.
DOI
10.1109/IROS.2012.6385741
ISBN
9781467317375
Appears in Collections:
엘텍공과대학 > 컴퓨터공학과 > Journal papers
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