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Model-Based Estimation of Off-Highway Road Geometry using Single-Axis LADAR and Inertial Sensing
Abstract This paper applies some previously studied …
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.
he sensor pose for each range measurement.  +
Authors Lars B. Cremean and Richard M. Murray  +
ID 2005u  +
Source To appear, 2006 International Conference on Robotics and Automation (ICRA)  +
Tag cm06-icra  +
Title Model-Based Estimation of Off-Highway Road Geometry using Single-Axis LADAR and Inertial Sensing +
Type Conference Paper  +
Categories Papers
Modification date
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15 May 2016 06:17:44  +
URL
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http://www.cds.caltech.edu/~murray/preprints/cm06-icra.pdf  +
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Model-Based Estimation of Off-Highway Road Geometry using Single-Axis LADAR and Inertial Sensing + Title
 

 

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