Conference paper:
Andrea Censi, Luca Marchionni, and Giuseppe Oriolo.
Simultaneous maximum-likelihood calibration of robot and sensor parameters.
In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Pasadena, CA, May 2008.
pdfdoi
video
supp. material
slides
bibtex
@inproceedings{censi08calib,
author = "Censi, Andrea and Marchionni, Luca and Oriolo, Giuseppe",
doi = "10.1109/ROBOT.2008.4543516",
title = "Simultaneous maximum-likelihood calibration of robot and sensor parameters",
url = "http://purl.org/censi/2007/calib",
booktitle = "Proceedings of the {IEEE} International Conference on Robotics and Automation ({ICRA})",
year = "2008",
month = "May",
slides = "http://purl.org/censi/research/2008-icra-calibration-slides.pdf",
video = "http://purl.org/censi/research/2008-icra-calibration-video.mpg",
address = "Pasadena, CA",
pdf = "http://purl.org/censi/research/2008-icra-calibration.pdf",
abstract = "For a differential-drive mobile robot equipped with an on-board range sensor, there are six parameters to calibrate: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot frame. This paper describes a method for calibrating all six parameters at the same time, without the need for external sensors or devices. Moreover, it is not necessary to drive the robot along particular trajectories. The available data are the measures of the angular velocities of the wheels and the range sensor readings. The maximum-likelihood calibration solution is found in a closed form."
}
Journal paper:
Andrea Censi, Antonio Franchi, Luca Marchionni, and Giuseppe Oriolo.
Simultaneous calibration of odometry and sensor parameters for mobile robots.
IEEE Transactions on Robotics, 29(2):475–492, April 2013.
pdfdoi supp. material
bibtex
@article{censi13joint,
author = "Censi, Andrea and Franchi, Antonio and Marchionni, Luca and Oriolo, Giuseppe",
doi = "10.1109/TRO.2012.2226380",
title = "Simultaneous calibration of odometry and sensor parameters for mobile robots",
url = "http://purl.org/censi/2012/joint_calibration",
journal = "IEEE Transactions on Robotics",
year = "2013",
number = "2",
month = "April",
volume = "29",
sortyear = "2011",
pdf = "http://purl.org/censi/research/2012-joint_calibration.pdf",
pages = "475--492"
}
Abstract -- Consider a differential-drive mobile robot equipped with an on-board exteroceptive sensor that can estimate its own motion, e.g., a range-finder. Calibration of this robot involves estimating six parameters: three for the odometry (radii and distance between the wheels), and three for the pose of the sensor with respect to the robot. After analyzing the observability of this problem, this paper describes a method for calibrating all parameters at the same time, without the need for external sensors or devices, using only the measurement of the wheels velocities and the data from the exteroceptive sensor. Moreover, the method does not require the robot to move along particular trajectories. Simultaneous calibration is formulated as a maximum-likelihood problem and the solution is found in a closed form. Experimental results show that the accuracy of the proposed calibration method is very close to the attainable limit.
Additional materials
The software and sensor logs is available for download:
