Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Autonomous Robots
Erschienen in: Autonomous Robots 2/2017

30.01.2016

Learning autonomous behaviours for the body of a flexible surgical robot

verfasst von: Danilo Bruno, Sylvain Calinon, Darwin G. Caldwell

Erschienen in: Autonomous Robots | Ausgabe 2/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This paper presents a novel strategy to learn a positional controller for the body of a flexible surgical manipulator used for minimally invasive surgery. The manipulator is developed within the STIFF-FLOP European project and is targeted for a laparoscopic use in remote areas of the abdominal region that are not easily accessible by means of currently available rigid tools. While the surgeon controls the end-effector during the task, the flexible body of the manipulator needs to be displaced to enter inside constrained spaces by efficiently exploiting its flexibility, without touching vital organs and structures. The proposed algorithm exploits the instruments of machine learning within the programming by demonstrations paradigm to produce a statistical model of the natural movements of the surgeon during the task. The gathered information is then reused to determine a controller in the null space of the robot that does not interfere with the surgeon task and displaces the robot body within the available space in a fully automated manner.
Vorheriger Artikel Stochastic mobility prediction of ground vehicles over large spatial regions: a geostatistical approach
Nächster Artikel Head stabilization in a humanoid robot: models and implementations

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren
Anhänge
Nur mit Berechtigung zugänglich
Literatur
Bruno, D., Calinon, S., & Caldwell, D. G. (2014). Null space redundancy learning for a flexible surgical robot. In IEEE international conference on robotics and automation (ICRA) (pp. 2443–2448). Hong Kong.
Calinon, S., Bruno, D., & Caldwell, D. G. (2014a). A task-parameterized probabilistic model with minimal intervention control. In IEEE international conference on robotics and automation (ICRA) (pp. 3339–3344). Hong Kong.
Calinon, S., Bruno, D., Malekzadeh, M. S., Nanayakkara, T., & Caldwell, D. G. (2014b). Human-robot skills transfer interfaces for a flexible surgical robot. Computer Methods and Programs in Biomedicine, 116(2), 81–96. Special issue on new methods of human-robot interaction in medical practice.
Calinon, S., D’halluin, F., Sauser, E. L., Caldwell, D. G., & Billard, A. G. (2010). Learning and reproduction of gestures by imitation: An approach based on hidden Markov model and Gaussian mixture regression. IEEE Robotics and Automation Magazine, 17(2), 44–54.CrossRef
Cianchetti, M., Ranzani, T., Gerboni, G., De Falco, I., Laschi, C., & Menciassi, A. (2013). Stiff-flop surgical manipulator: mechanical design and experimental characterization of the single module. In IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 3567–3581).
Flash, T., & Hogan, N. (1985). The coordination of the arm movements: An experimentally confirmed mathematical model. Neurology, 5(7), 1688–1703.
Gauvain, J.-L., & Lee, C.-H. (1994). Maximum a posteriori estimation for multivariate gaussian mixture observations of markov chians. IEE Transactions on Speech and Audio Processing, 2(2), 291–298.CrossRef
Gielniak, M. J., Liu, C. K., & Thomaz, A. L. (2011). Task-aware variations in robot motion. In IEEE international conference on robotics and automation (ICRA) (pp. 3921–3927).
Jiang, A., Ataollahi, A., Althoefer, K., Dasgupta, P., & Nanayakkara, T. (2012a). A variable stiffness joint by granular jamming. In ASME international design engineering technical conference and computers and information in engineering conference (IDETC/CIE) (pp. 267–275).
Jiang, A., Xynogalas, G., Dasgupta, P., Althoefer, K., & Nanayakkara, T. (2012b). Design of a variable stiffness flexible manipulator with composite granular jamming and membrane coupling. In IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 2922–2927).
Kulis, B., & Jordan, M. I. (2012). Revisiting k-means: New algorithms via bayesian nonparametrics. In Proceedings of the international conference on machine learning (ICML), Edimburgh.
Lee, D., & Ott, C. (2011). Incremental kinesthetic teaching of motion primitives using the motion refinement tube. Autonomous Robots, 31(2), 115–131.CrossRef
Lobaton, E., Fu, J., Torres, L., & Alterovitz, R. (2013). Continuous shape estimation of continuum robots using x-ray images. In IEEE international conference on robotics and automation (ICRA) (pp. 725–732).
Lyons, L., Webster, R., & Alterovitz, R. (2010). Planning active cannula configurations through tubular anatomy. In IEEE international conference on robotics and automation (ICRA) (pp. 2082–2087). Anchorage, AK.
MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the symposium on mathematical statistics and probability (pp. 281–297), Berkeley: University of California Press.
Malekzadeh, M. S., Calinon, S., Bruno, D., & Caldwell, D. G. (2014). Learning by imitation with the STIFF-FLOP surgical robot: A biomimetic approach inspired by octopus movements. Robotics and Biomimetics Special Issue on Medical Robotics, 1(13), 1–15.
Nordmann, A., Emmerich, C., Ruether, S., Lemme, A., Wrede, S., & Steil, J. (2012). Teaching nullspace constraints in physical human-robot interaction using reservoir computing. In IEEE international conference on robotics and automation (ICRA) (pp. 1868–1875).
Quinlan, S., & Khatib, O. (1993). Elastic bands: Connecting path planning and control. In Proceedings of the international conference on robotics and automation (ICRA) (pp. 802–807).
Rajiv Ranganatan, A. A., & Mussa-Ivaldi, F. A. (2013). Learning to be lazy, exploiting redundancy in a novel task to minimize movement-related effort. Journal of Neuroscience, 33(7), 2754–2760.CrossRef
Reiter, A., Goldman, R. E., Bajo, A., Iliopoulos, K., Simaan, N., & Allen, P. K. (2011). A learning algorithm for visual pose estimation of continuum robots. In IEEE international conference on robotics and automation (ICRA) (pp. 2390–2396), San Francisco, CA.
Song, M., & Wang, H. (2005). Highly efficient incremental estimation of Gaussian mixture models for online data stream clustering. In Proceedings of SPIE: Intelligent computing—theory and applications III (Vol. 5803, pp. 174–183).
Sternad, D., Abe, M. O., Hu, X., & Mueller, H. (2011). Neuromotor noise, error tolerance and velocity-dependent costs in skilled performance. PLoS Computational Biology, 7(9), e1002159.CrossRef
Todorov, E., & Jordan, M. I. (2002). A minimal intervention principle for coordinated movement. In Advances in neural information processing systems (NIPS) (pp. 27–34).
Towell, C., Howard, M., & Vijayakumar, S. (2010). Learning nullspace policies. In Proceedings of IEEE/RSJ international conference on intelligent robots and systems (IROS) (pp. 241–248).
Van Den Berg, J., Miller, S., Duckworth, D., Hu, H., Wan, A., Fu, X., et al. (2010). Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations. In IEEE international conference on robotics and automation (ICRA) (pp. 2074–2081). Anchorage, AK.
Yang, X., Zhu, C., Yang, M., Hu, H., Xia, L., & Pan, K. (2012). Laparoscopic radical resection for rectal cancer. Translational Gastrointestinal Cancer, 1(3), 255–271.
Zelman, I., Titon, M., Yekutieli, Y., Hanassy, S., Hochner, B., & Flash, T. (2013). Kinematic decomposition and classification of octopus arm movements. Frontiers in Computational Neuroscience, 7, 60.CrossRef
Zhang, Z., Chen, C., Sun, J., & Chan, K. L. (2003). EM algorithms for Gaussian mixtures with split-and-merge operation. Pattern Recognition, 36(9), 1973–1983.CrossRefMATH
Metadaten
Titel
Learning autonomous behaviours for the body of a flexible surgical robot
verfasst von
Danilo Bruno
Sylvain Calinon
Darwin G. Caldwell
Publikationsdatum
30.01.2016
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 2/2017
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-016-9544-6

Weitere Artikel der Ausgabe 2/2017

Autonomous Robots 2/2017 Zur Ausgabe

OriginalPaper

RBDL: an efficient rigid-body dynamics library using recursive algorithms

OriginalPaper

An accurate and efficient navigation system for omnidirectional robots in industrial environments

OriginalPaper

Spinal joint compliance and actuation in a simulated bounding quadruped robot

OriginalPaper

Dynamically feasible, energy efficient motion planning for skid-steered vehicles

OriginalPaper

Spatio-temporal stiffness optimization with switching dynamics

OriginalPaper

The speed graph method: pseudo time optimal navigation among obstacles subject to uniform braking safety constraints

Neuer Inhalt

    Bildnachweise