Simplified adaptive path planning for percutaneous needle insertions

Ederson Dorileo 1 Abdulrahman Albakri 1 Nabil Zemiti 1 Philippe Poignet 1
1 DEXTER - Conception et commande de robots pour la manipulation
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Needle placement errors can mitigate the effectiveness of the diagnosis or the therapy, sometimes with catastrophic outcomes. Previous design of a simplified model for needle deflection estimation was motivated by the clinical constraints of ARCS (Abdomino-pelvic Robotic-driven slightly flexible needle insertion performed in CT/MRI-guided Scenario). We present in this work, the validation results for the needle deflection prediction model. Its robustness is evaluated under an unknown context such as a different robotic platform, facing uncertainties conditions not conceived previously in the model's confection. In addition, the work presents the development and validation experiments of an adaptive path planner that uses the model as predictor's strategy. It provides pre-operative planning assistance, as well as intra-operative decision-making support. The experiments results showed average error around 1mm for the pre-operative planning and the intra-operative replanning approach showed to be very robust to correct the initial predictions, showing average error smaller than 1 mm.
Type de document :
Communication dans un congrès
ICRA: International Conference on Robotics and Automation, May 2015, Seattle, WA, United States. 32nd IEEE International Conference on Robotics and Automation, pp.1782-1788, 2015, 〈http://icra2015.org〉. 〈10.1109/ICRA.2015.7139429〉
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-01275360
Contributeur : Nabil Zemiti <>
Soumis le : mercredi 17 février 2016 - 12:42:26
Dernière modification le : lundi 17 décembre 2018 - 11:36:04

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LIRMM | DEXTER | MIPS | UNIV-MONTPELLIER

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Ederson Dorileo, Abdulrahman Albakri, Nabil Zemiti, Philippe Poignet. Simplified adaptive path planning for percutaneous needle insertions. ICRA: International Conference on Robotics and Automation, May 2015, Seattle, WA, United States. 32nd IEEE International Conference on Robotics and Automation, pp.1782-1788, 2015, 〈http://icra2015.org〉. 〈10.1109/ICRA.2015.7139429〉. 〈lirmm-01275360〉

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