Physiological Organ Motion Prediction And Compensation Based On Multi-rate Delayed And Unregistered Measurements In Robot-assisted Surgery And Therapy
Physiological motion makes performing a surgical or therapeutic procedure more difficult for the physician. In heart surgery, the heart is stopped as it is too difficult for the surgeon to follow the heart’s beating motion and perform a surgical task. In radiation therapy, respiration causes the cancerous tissue to move, rendering the therapy less effective and possibly damaging to healthy tissue. This paper focuses on controlling a robot, which is used to perform the surgery or therapy, to compensate for the physiological motion along the surgical tool’s axis such that the point of interest (POI) on the organ becomes stationary relative to the robot. The difficulties in creating such a system lies in the measurement of the POI’s and robot’s positions via different sensors that are unregistered, have different measurement rates, and have data acquisition and processing delays. This paper presents Kalman filter based estimation of the organ motion despite the large data acquisition/processing delays and low update rates inherent in some measurements used for robot control in robot-assisted surgeries and therapies. This paper also proposes control systems that compensate for the organ motion despite the delayed, multi-rate and unregistered sensor data allowing the physician to perform a therapeutic or surgical procedure with a teleoperated robot on seemingly stationary POI.