5 research outputs found

    Event-based device-behavior switching in surgical human-robot interaction

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    In present days, the number of application in which robots and users share the same workspace is increasing, as long as the need of cooperation between them. To achieve a smooth cooperation, in particular in surgical applications, the robot needs to timely change its behavior to adapt to the needs of the user. In this work, a simplified scenario for neurosurgery was defined in which the user interacts with the robot through a Graphical User Interface (GUI) and by touching the robot links and, based to those events and on the current status, different control modes are enabled in the high level controller we developed, such as autonomous, cooperative and teleoperation. Experiments were performed to measure the performances and safety of the developed high level controller in handling the transitions between two states by checking the continuity of data from the robot and from an external measurement system. Results proved that the trajectories of the end effector and links during the switching phase are continuous and thus the modular high level controller developed switches control safely without undesired deviation from desired course

    Convergence Analysis of an Iterative Targeting Method for Keyhole Robotic Surgery

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    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
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