View source for Model-Based Estimation of Off-Highway Road Geometry using Single-Axis LADAR and Inertial Sensing

{{HTDB paper
| authors = Lars B. Cremean and Richard M. Murray
| title = Model-Based Estimation of Off-Highway Road Geometry using Single-Axis LADAR and Inertial Sensing
| source = To appear, 2006 International Conference on Robotics and Automation (ICRA)
| year = 2005
| type = Conference Paper
| funding = Honeywell
| url = http://www.cds.caltech.edu/~murray/preprints/cm06-icra.pdf
| abstract = 
This paper applies some previously studied extended
Kalman filter techniques for planar road geometry
estimation to the domain of autonomous navigation of offhighway
vehicles. In this work, a clothoid model of the road
geometry is constructed and estimated recursively based on
road features extracted from single-axis LADAR range measurements.
We present a method for feature extraction of the
road centerline in the image plane, and describe its application
to recursive estimation of the road geometry. We analyze
the performance of our method against simulated motion of
varied road geometries and against recorded data from previous
autonomous navigation runs. Our method accomodates full 6
DOF motion of the vehicle as it navigates, constructs consistent
estimates of the road geometry with respect to a fixed global
reference frame, and requires an estimate of the sensor pose
for each range measurement.
| flags = 
| tag = cm06-icra
| id = 2005u
}}