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Title:
BioCD: an efficient algorithm for self-collision and distance computation between highly articulated molecular models.
Author(s):
V. Ruiz de Angelo, J. Cortés and T. Siméon.
Main site:
LAAS-CNRS
Restrictions:
Public
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 considers
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.
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