Abstract-This paper presents a predictive control approach to active mechanical filtering of complex, periodic motions of organs induced by respiration or heart beating in robotized surgery. Two different predictive control schemes are proposed for the compensation of respiratory motions or cardiac motions.For respiratory motions, the periodic property of the disturbance has been included into the input-output model of the controlled system so as to have the robotic system learn and anticipate perturbation motions. A new cost function is proposed for the unconstrained generalized predictive controller (GPC) where reference tracking is decoupled from the rejection of predictable periodic motions.Cardiac motions are more complex since they are the combination of two periodic non-harmonic components. An adaptive disturbance predictor is proposed which outputs future predicted disturbance values. These predicted values are used to anticipate the disturbance by using the predictive feature of a regular GPC.Experimental results are presented on a laboratory testbed and in vivo on pigs. They demonstrate the effectiveness of the two proposed methods to compensate complex physiological motion.

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Percutaneous procedures are among the developing minimally invasive techniques to treat cancerous diseases of the digestive system. They require a very accurate targeting of the organs, achieved by the combination of tactile sensing and medical imaging. In this paper, we study the forces involved during in vivo percutaneous procedures for the development of a force feedback needle insertion robotic system as well as the development of a realistic simulation device. The paper presents different conditions (manual and robotic insertions) and different organs (liver and kidney). Finally, we review some bio-mechanical models of the literature in the light of our measurements.

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Abslracf-This paper prisents. first in-vivo results of heating heart tracking with a surgical robot arm in off-pump cardiac surgery. The tracking is performed in a 2D visual servoing scheme using a 500 frame per second video camera Heart motion is measured by means of active optical markers that are put onto the heart surface. Amplitude of the motion is evaluated along the 'two axis of the image referenee~frame. This is a complex and fast motion that mainly reflects the influence of both the respiratory -motion and the electrc-mechanikl activity of the myocardium. A model predictive controller is setup to track the two degrees of freedom of the observed motion by computing velocities for two of the robot joints. The servoing scheme takes advanlage OC the ability of predictive control lo anticipate over future references provided they are known or they can be predicted. An adaptive observer is defined along with a simple cardiac model to estimate the two components of the heart motion. The predictions are then ' fed into the controller references and it is shown that the tracktng i '

Off-pump totally endoscopic coronary artery bypass grafting is a milestone for cardiac surgery, and still a technical challenge. Indeed, the fast and complex cardiac motion makes this operating method technically demanding. Therefore, several robotic systems have been designed to assist the surgeons by compensating for the cardiac motion and providing a virtually motionless operating area. In the proposed systems, the servoing schemes often take advantage of a prediction algorithm that supplies the controller with some future heart motion. This prediction enlarges the control-loop bandwidth, thus allowing a better motion compensation. Obviously, improving the prediction accuracy will lead to better motion-compensation results. Thus, a current challenge in computer-assisted cardiac surgery research is the design of efficient heart-motion-prediction algorithms. In this paper, a detailed survey of the main existing prediction approaches is given and a classification is provided. Then, a novel prediction technique based on amplitude modulation is proposed, and compared with other techniques using in vivo collected datasets. A final discussion summarizes the main features of all the proposed approaches.

An alternative approach to standard computed torque with feedback linearization is proposed in this work to control cable-driven parallel robots (CDPRs) with highly flexible cables. Exteroceptive feedback is used to measure the end-effector Cartesian position at a high sampling rate. Stability is demonstrated using singular perturbation theory. The proposed control scheme is experimentally validated on a planar 3-degree-of-freedom CDPR and its efficiency is assessed by comparison to a simple kinematic control law.

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