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Unified Motion-Based Calibration of Mobile Multi-Sensor Platforms With Time Delay Estimation
Department of Computer, Control, and Management Engineering “Antonio Ruberti” Sapienza, University of Rome, Rome, Italy.
Örebro University, School of Science and Technology. (Center of Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-2953-1564
Örebro University, School of Science and Technology. (Center of Applied Autonomous Sensor Systems (AASS))ORCID iD: 0000-0002-6013-4874
Department of Computer, Control, and Management Engineering “Antonio Ruberti” Sapienza, University of Rome, Rome, Italy.
2019 (English)In: IEEE Robotics and Automation Letters, ISSN 2377-3766, E-ISSN 1949-3045, Vol. 4, no 2, p. 902-909Article in journal (Refereed) Published
Abstract [en]

The ability to maintain and continuously update geometric calibration parameters of a mobile platform is a key functionality for every robotic system. These parameters include the intrinsic kinematic parameters of the platform, the extrinsic parameters of the sensors mounted on it, and their time delays. In this letter, we present a unified pipeline for motion-based calibration of mobile platforms equipped with multiple heterogeneous sensors. We formulate a unified optimization problem to concurrently estimate the platform kinematic parameters, the sensors extrinsic parameters, and their time delays. We analyze the influence of the trajectory followed by the robot on the accuracy of the estimate. Our framework automatically selects appropriate trajectories to maximize the information gathered and to obtain a more accurate parameters estimate. In combination with that, our pipeline observes the parameters evolution in long-term operation to detect possible values change in the parameters set. The experiments conducted on real data show a smooth convergence along with the ability to detect changes in parameters value. We release an open-source version of our framework to the community.

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 4, no 2, p. 902-909
Keywords [en]
Calibration and Identification
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:oru:diva-72756DOI: 10.1109/LRA.2019.2892992ISI: 000458182100012OAI: oai:DiVA.org:oru-72756DiVA, id: diva2:1291440
Note

Funding Agency:

Semantic Robots Research Profile - Swedish Knowledge Foundation (KKS) 

Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-02-25Bibliographically approved

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Andreasson, HenrikStoyanov, Todor

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