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Calibrating distance sensors for terrestrial applications without groundtruth information
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0001-6868-2210
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-4310-7938
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.ORCID iD: 0000-0002-0079-9049
2017 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 17, no 12, 3698-3709 p., 7911206Article in journal (Refereed) Published
Abstract [en]

This paper describes a new calibration procedure for distance sensors that does not require independent sources of groundtruth information, i.e., that is not based on comparing the measurements from the uncalibrated sensor against measurements from a precise device assumed as the groundtruth. Alternatively, the procedure assumes that the uncalibrated distance sensor moves in space on a straight line in an environment with fixed targets, so that the intrinsic parameters of the statistical model of the sensor readings are calibrated without requiring tests in controlled environments, but rather in environments where the sensor follows linear movement and objects do not move. The proposed calibration procedure exploits an approximated expectation maximization scheme on top of two ingredients: an heteroscedastic statistical model describing the measurement process, and a simplified dynamical model describing the linear sensor movement. The procedure is designed to be capable of not just estimating the parameters of one generic distance sensor, but rather integrating the most common sensors in robotic applications, such as Lidars, odometers, and sonar rangers and learn the intrinsic parameters of all these sensors simultaneously. Tests in a controlled environment led to a reduction of the mean squared error of the measurements returned by a commercial triangulation Lidar by a factor between 3 and 6, comparable to the efficiency of other state-of-the art groundtruth-based calibration procedures. Adding odometric and ultrasonic information further improved the performance index of the overall distance estimation strategy by a factor of up to 1.2. Tests also show high robustness against violating the linear movements assumption.

Place, publisher, year, edition, pages
IEEE, 2017. Vol. 17, no 12, 3698-3709 p., 7911206
Keyword [en]
Calibration, Laser radar, Robot sensing systems, Mobile robots, Time measurement expectation maximization, distance sensors, intrinsic sensors calibration, heteroscedastic models, simultaneous sensors calibration, triangulation lidars, ultrasonic sensors, odometry
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-63189DOI: 10.1109/JSEN.2017.2697850ISI: 000402123400012Scopus ID: 2-s2.0-8502174995OAI: oai:DiVA.org:ltu-63189DiVA: diva2:1091864
Note

Validerad;2017;Nivå 2;2017-05-29 (rokbeg)

Available from: 2017-04-28 Created: 2017-04-28 Last updated: 2017-09-13Bibliographically approved

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Publisher's full textScopushttp://ieeexplore.ieee.org/document/7911206/

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