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Adaptive locally linear kinematic modelling of concentric tube robots

Fagogenis, G; Bergeles, C; Dupont, PE; (2016) Adaptive locally linear kinematic modelling of concentric tube robots. In: Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on. (pp. pp. 4324-4329). IEEE Green open access

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Abstract

Concentric tube robots comprise telescopic precurved elastic tubes. The robot's tip and shape are controlled via relative tube motions, i.e. tube rotations and translations. Non-linear interactions between the tubes, e.g. friction and torsion, as well as uncertainty in the physical properties of the tubes themselves, e.g. the Young’s modulus, curvature, or stiffness, hinder accurate kinematic modelling. In this paper, we present a machine-learning-based methodology for kinematic modelling of concentric tube robots and in situ model adaptation. Our approach is based on Locally Weighted Projection Regression (LWPR). The model comprises an ensemble of linear models, each of which locally approximates the original complex kinematic relation. LWPR can accommodate for model deviations by adjusting the respective local models at run-time, resulting in an adaptive kinematics framework. We evaluated our approach on data gathered from a three-tube robot, and report high accuracy across the robot's configuration space.

Type: Proceedings paper
Title: Adaptive locally linear kinematic modelling of concentric tube robots
Event: IROS 2016: IEEE/RSJ International Conference on Intelligent Robots and Systems, 9-14 October 2016, Daejeon, South Korea
Location: Korea
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/IROS.2016.7759636
Publisher version: https://doi.org/10.1109/IROS.2016.7759636
Language: English
Additional information: © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Adaptation models, Kinematics, Electron tubes, Robot kinematics, Kernel, Robot sensing systems
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1503367
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