Publication

BioCD : An efficient algorithm for self-collision and distance computation between highly articulated molecular models

Conference Article

Conference

Robotics: Science and Systems Conference (RSS)

Edition

I

Pages

141-148

Doc link

http://www.roboticsproceedings.org/rss01/p32.pdf

File

Download the digital copy of the doc pdf document

Abstract

This paper describes an efficient approach to (self) collision detection and distance computations for complex articulated mechanisms such as molecular chains. The proposed algorithm called BioCD is particularly designed for sampling-based motion planning on molecular models described by long kinematic chains possibly including cycles. The algorithm con s that the kinematic chain is structured into a number of rigid groups articulated by preselected degrees of freedom. This structuration is exploited by a two-level spatially-adapted hierarchy. The proposed algorithm is not limited to particular kinematic topologies and allows good collision detection times. BioCD is also tailored to deal with the particularities imposed by the molecular context on collision detection. Experimental results show the effectiveness of the proposed approach which is able to process thousands of (self) collision tests per second on flexible protein models with up to hundreds of degrees of freedom.

Categories

robots.

Author keywords

collision detection, biochemistry, proteins

Scientific reference

V. Ruiz de Angulo, J. Cortés and T. Simeon. BioCD : An efficient algorithm for self-collision and distance computation between highly articulated molecular models, I Robotics: Science and Systems Conference, 2005, Cambridge, USA, in Robotics: Science and Systems, pp. 141-148, 2005, MIT Press.