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Statistical modeling and calibration of triangulation Lidars
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.
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Signals and Systems.
Number of Authors: 3
2016 (English)In: ICINCO 2016: Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics / [ed] Peaucelle D.,Gusikhin O.,Madani K, SciTePress, 2016, 308-317 p.Conference paper, (Refereed)
Abstract [en]

We aim at developing statistical tools that improve the accuracy and precision of the measurements returned by triangulation Light Detection and Rangings (Lidars). To this aim we: i) propose and validate a novel model that describes the statistics of the measurements of these Lidars, and that is built starting from mechanical considerations on the geometry and properties of their pinhole lens - CCD camera systems; ii) build, starting from this novel statistical model, a Maximum Likelihood (ML) / Akaike Information Criterion (AIC) -based sensor calibration algorithm that exploits training information collected in a controlled environment; iii) develop ML and Least Squares (LS) strategies that use the calibration results to statistically process the raw sensor measurements in non controlled environments. The overall technique allowed us to obtain empirical improvements of the normalized Mean Squared Error (MSE) from 0.0789 to 0.0046

Place, publisher, year, edition, pages
SciTePress, 2016. 308-317 p.
National Category
Control Engineering
Research subject
Control Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-62315ISBN: 9789897581984 (print)OAI: oai:DiVA.org:ltu-62315DiVA: diva2:1078682
Conference
13th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2016, Lisbon, Portugal, 29-31 July 2016
Available from: 2017-03-06 Created: 2017-03-06 Last updated: 2017-04-28Bibliographically approved

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