Model Based Control Algorithms for Robotic Assisted Beating Heart Surgery

Abstract

Robotics technology promises an enhanced way of performing off-pump coronary artery bypass graft (CABG) surgery. In the robotic-assisted CABG surgery, surgeon performs the operation with intelligent robotic instruments controlled through teleoperation that replace conventional surgical tools. The robotic tools actively cancel the relative motion between the surgical instruments and the point-of-interest on the beating heart, in contrast to traditional off-pump CABG where the heart is passively constrained to dampen the beating motion. As a result, the surgeon operates on the heart as if it were stationary. This algorithm is called active relative motion canceling (ARMC). In this paper, the use of biological signals to achieve better motion canceling in the model-based intelligent ARMC algorithm is presented. Also, integration of arrythmia detection and handling with the ARMC algorithm is proposed in order to provide safety over the system. Finally, tracking results of combined respiratory motion and heartbeat motion on a 3-DOF robotic test-bed system are reported.