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Coordinated control of a 3DOF cartesian robot and a shape memory alloy-actuated flexible needle for surgical interventions: a non-model-based control method

Published online by Cambridge University Press:  22 October 2021

Fan Liang
Affiliation:
Tianjin Key Laboratory of Information Sensing & Intelligent Control, Tianjin University of Technology and Education, Tianjin, China Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH 44106, USA
Bryan J. Traughber
Affiliation:
Department of Radiation Oncology, Pennsylvania State University, Hershey, PA 17033, USA
Tithi Biswas
Affiliation:
Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
Gordon Guo
Affiliation:
Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA
Raymond F. Muzic
Affiliation:
Department of Radiology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, OH 44106, USA Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
Tarun K. Podder*
Affiliation:
Department of Radiation Oncology, University Hospitals Seidman Cancer Center, Case Western Reserve University, Cleveland, OH 44106, USA Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA
*
*Corresponding author. E-mail: [email protected]

Summary

Success of any needle-based medical procedures depends on accurate placement of the needle at the target location. However, accurate targeting and control of flexible self-actuating (active) needle are challenging. We have developed a shape memory alloy-actuated flexible needle steered by a 3D Cartesian robot and performed a comparative study of four, non-model-based, coordinated control methodologies for the combined robot steering and flexible-needle insertion process for surgical interventions. Investigated four controllers are: proportional–integral–derivative (PID), PID with the cubic of positional error term (PID-P3), static PID sliding mode controller, and robust adaptive PID sliding mode controller (RAPID-SMC). Relative efficacies of these controllers are demonstrated by performing experiements using a tissue-mimicking soft material phantom. Results from experiments have reavealed that RAPID-SMC is superior to other three controllers.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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