Please use this identifier to cite or link to this item: https://doi.org/10.15480/336.4544
Title: Position Data of Offline Needle Steering
Language: English
Authors: Neidhardt, Maximilian 
Reinecke, Anton 
Rogalla, Antje  
Lehmann, Sascha 
Sprenger, Johanna 
Schlaefer, Alexander 
Schupp, Sibylle 
Issue Date: 7-Oct-2022
Abstract (english): 
"Automated needle steering in soft tissue" is an open problem in both surgery robotics and formal verification. Challenges that are common to both fields include the interaction between needle and tissue, which depends on the coupled effects of needle deflection, friction and force, and tissue deformation; navigation, collision avoidance, and path planning, which are faced with inhomogeneous, partially unknown tissue; and also adaptive updates and feedback, which are required in real time.
For each experiment, we record the feed of the needle in millimeters, the x, y, and z position of the needle in millimeters, and the rotation angle of the alignment of the angled needle tip in degree. The setup allows the needle to be pushed forwards and backward in the y direction.
The experiments we restrict to a two-dimensional setting, but three-dimensional position data are recorded. Accordingly, we execute only motion plans with half rotations by 180 degree rotations. We do not execute motion plans with backward movement. Also, we do not allow more than two rotations within one motion plan.
URI: http://hdl.handle.net/11420/13437
DOI: 10.15480/336.4544
Institute: Softwaresysteme E-16 
Medizintechnische und Intelligente Systeme E-1 
Document Type: Dataset
Project: I³-Lab - Modell-gestütztes maschinelles Lernen für die Weichgewebsmodellierung in der Medizin 
License: CC0 1.0 (Public Domain Dedication) CC0 1.0 (Public Domain Dedication)
Appears in Collections:Research Data TUHH

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