Ferro, Marco, Gaz, Claudio and Vendittelli, Marilena (2020) A framework for sensorless identification of needle-tissue interaction forces in robot-assisted biopsies. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), 2020 Workshop : Shared Autonomy : Learning and Control (SALC); 31 May - 31 Aug 2020, Paris, France (Held online). (Unpublished)

Abstract

Abstract— During teleoperated robot-assisted biopsies, force and visual feedback are fundamental to guarantee accuracy and safety in executing the task. To allow seamless introduction of the robot in the clinical flow, it is desirable to measure interaction forces without relying on dedicated, additional sensors. On the other hand, typical imaging systems do not offer a real-time 3D view of the remote site at the operator-side. In this document, we extend a previous work with two contributions: i) a sensorless needle-tissue interaction model identification algorithm; ii) a modular framework, interfaced with a virtual environment, offering a complete visualization of the procedure at the operator-side. The identification algorithm is validated on an isinglass-based phantom, while the framework is tested through the CoppeliaSim (former V-REP) software.

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