The aim of this study is to design and develop a robotic system capable of compensating a patient's periodic movement, such as a beating heart, breath-induced thoracic cavity motion, and able to avoid collisions in case of sudden and unexpected motions, caused by pain, tremor, or other diseases, during an in situ bioprinting process. Based on the previous work carried out on the IMAGObot platform (a 5 Degrees of Freedom robotic manipulator), the aim is to print on moving and non-planar surfaces, following the trajectory of a fiducial marker placed onto the patient, inside the robot workspace. For this purpose, a monocular vision system (featured by a webcam and fiducial markers positioned in the robot environment) and a software interface communicating with the robot controller were developed. The control algorithm was entirely developed in the Python environment using the OpenCV library for marker pose estimation and used to update the robot trajectory concerning the detected marker motion on LinuxCNC software. Moreover, in order to mimic the physiological displacement of a patient's rib cage due to breathing, a moving 3D-printed platform and a silicone chest phantom were fabricated. The motion compensation system was tested by regenerating a defect on the chest phantom during the respiratory phase through extrusion based in situ bioprinting.
Motion compensation system for robotic based in situ bioprinting to balance patient physiological movements
Fortunato G. M.;Bonatti A. F.;Batoni E.;Macaluso R.;Vozzi G.;De Maria C.
Ultimo
2022-01-01
Abstract
The aim of this study is to design and develop a robotic system capable of compensating a patient's periodic movement, such as a beating heart, breath-induced thoracic cavity motion, and able to avoid collisions in case of sudden and unexpected motions, caused by pain, tremor, or other diseases, during an in situ bioprinting process. Based on the previous work carried out on the IMAGObot platform (a 5 Degrees of Freedom robotic manipulator), the aim is to print on moving and non-planar surfaces, following the trajectory of a fiducial marker placed onto the patient, inside the robot workspace. For this purpose, a monocular vision system (featured by a webcam and fiducial markers positioned in the robot environment) and a software interface communicating with the robot controller were developed. The control algorithm was entirely developed in the Python environment using the OpenCV library for marker pose estimation and used to update the robot trajectory concerning the detected marker motion on LinuxCNC software. Moreover, in order to mimic the physiological displacement of a patient's rib cage due to breathing, a moving 3D-printed platform and a silicone chest phantom were fabricated. The motion compensation system was tested by regenerating a defect on the chest phantom during the respiratory phase through extrusion based in situ bioprinting.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.