Model-based estimation of off-highway road geometry using single-axis LADAR and inertial sensing
- Creators
- Cremean, Lars B.
- Murray, Richard M.
Abstract
This paper applies some previously studied extended Kalman filter techniques for planar road geometry estimation to the domain of autonomous navigation of off-highway 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 closed-loop detection, tracking and following of desert roads. 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.
Additional Information
© 2006 IEEE. Issue Date: 15-19 May 2006. Date of Current Version: 26 June 2006.Attached Files
Published - Cremean2006p96952008_Ieee_International_Conference_On_Robotics_And_Automation_Vols_1-9.pdf
Files
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Additional details
- Eprint ID
- 22098
- Resolver ID
- CaltechAUTHORS:20110209-135047997
- Created
-
2011-03-10Created from EPrint's datestamp field
- Updated
-
2021-11-09Created from EPrint's last_modified field
- Series Name
- IEEE International Conference on Robotics and Automation
- Other Numbering System Name
- INSPEC Accession Number
- Other Numbering System Identifier
- 9120493