Convergence Analysis of an Iterative Targeting Method for Keyhole Robotic Surgery
| Autor: | Jörg Raczkowsky, Mirko Daniele Comparetti, Elena De Momi, Tim Beyl, Giancarlo Ferrigno, Mirko Kunze |
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| Rok vydání: | 2014 |
| Předmět: |
Robotic Surgery
Iterative Targeting Neurosurgery Computer science lcsh:Electronics DATA processing & computer science lcsh:TK7800-8360 Calibration matrix lcsh:QA75.5-76.95 Computer Science Applications Artificial Intelligence Control theory Robustness (computer science) Robot Robotic surgery lcsh:Electronic computers. Computer science ddc:004 Keyhole Software Simulation |
| Zdroj: | International journal of advanced robotic systems, 11 (1), Art.Nr. 60 International Journal of Advanced Robotic Systems, Vol 11 (2014) International Journal of Advanced Robotic Systems |
| ISSN: | 1729-8814 1729-8806 |
| DOI: | 10.5772/58250 |
| Popis: | In surgical procedures, robots can accurately position and orient surgical instruments. Intraoperatively, external sensors can localize the instrument and compute the targeting movement of the robot, based on the transformation between the coordinate frame of the robot and the sensor. This paper addresses the assessment of the robustness of an iterative targeting algorithm in perturbed conditions. Numerical simulations and experiments (with a robot with seven degrees of freedom and an optical tracking system) were performed for computing the maximum error of the rotational part of the calibration matrix, which allows for convergence, as well as the number of required iterations. The algorithm converges up to 50 degrees of error within a large working space. The study confirms the clinical relevance of the method because it can be applied on commercially available robots without modifying the internal controller, thus improving the targeting accuracy and meeting surgical accuracy requirements. |
| Databáze: | OpenAIRE |
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