Home

About

Advanced Search

Browse by Discipline

Scientific Societies

E-print Alerts

Add E-prints

E-print Network
FAQHELPSITE MAPCONTACT US


  Advanced Search  

 
Robust and Efficient Computation of the Closest Point on a Spline Curve
 

Summary: Robust and Efficient Computation of the
Closest Point on a Spline Curve
Hongling Wang, Joseph Kearney, and Kendall Atkinson
Abstract. Parametric cubic spline curves are commonly used to
model the geometry of road surfaces in real-time driving simulators.
Roads are represented by space curves that define a curvilinear frame
of reference in which three-dimensional points are expressed in coordi-
nates of distance along the curve, offset from the central axis, and loft
from the road surface. Simulators must map from global Cartesian
coordinates to local road coordinates at very high frequencies. A key
component in this mapping is the computation of the closest point on
the central axis of the road to a three-dimensional point expressed in
Cartesian coordinates. The paper investigates a two-step method that
exploits the complementary strengths of two optimization techniques:
Newton's method and quadratic minimization.
1. Introduction
Parametric cubic spline curves provide a natural basis for modeling the
geometry of road surfaces in real-time driving simulators. The road model
is used by programs that control the behavior of autonomous vehicles and
pedestrians populating the virtual urban environment. In many simula-

  

Source: Atkinson, Kendall - Departments of Computer Science & Mathematics, University of Iowa
Kearney, Joseph K. - Department of Computer Science, University of Iowa

 

Collections: Computer Technologies and Information Sciences