This article proposes a control scheme for robot assisted laser osteotomy. Laser osteotomy consists in cutting a bone precisely with a laser. To achieve accurate cuts the laser has to be precisely sent to a desired pose with respect to the bone. In the proposed approach, a robot is used to position an end-effector with a scanhead, which deflects the cutting laser. The poses of the laser and of the bone are measured thanks to an optical tacking system which tracks the positions of optical markers placed on the bone and on the scanhead. The control of the robot is then performed thanks to a position-based visual servoing control scheme. In the case of bones affected by breathing motions, for instance the thorax bones, this control scheme is enhanced with a learning algorithm in order to compensate breathing motions. The main contribution of this paper is this control algorithm for motions compensation.

The proposed robotic system provides the surgeon with an augmented sensation of the interaction forces between the instrument and the organ. Such a system aims at increasing the surgeon's dexterity for tasks requiring that only small forces be applied on the organ (eg. for micro-surgery). In the proposed setup, the surgeon manipulates a handle mounted on the instrument. This is a comanipulation system because the surgeon and the robot simultaneously manipulate the instrument. The proposed control scheme allows an augmented force control: the control law ensures that the instrument applies on the organ the same forces that the surgeon applies on the handle but decreased by a scale factor. As a consequence, the forces sensed by the surgeon are the forces between the instrument and the organ amplified by a scale factor. This control scheme is proved stable thanks to a passivity study. Indeed, passivity analysis is a useful tool for the stability analysis of a robot interacting with the environment. Experimental results are presented on a robot dedicated to minimally invasive surgery.

This paper presents a force feedback control scheme for the compensation of periodic motions of organs induced by respiration or heartbeat in minimally invasive robotized surgery. It applies surgical tasks involving a contact between an instrument and a moving organ. It is well known that conventional force control allows for compensating the motion of the environment thanks to its natural disturbance rejection capabilities. However, as experimentally evidenced in the first part of this paper, bandwidth limitations do not allow for exact disturbance rejection. Therefore, in addition to a conventional inner force feedback control loop, an outer control loop based on iterative learning control (ILC) is implemented. It is aimed at compensating the physiological motions, based on the hypothesis that the disturbance is periodic. The transient performances of this ILC controller are improved thanks to a wavelet transform-based approach and conclusive experiments are finally presented, evidencing that the tracking performance under cyclic disturbances is significantly improved.

In this article, the problem of force feedback control of kinematically constrained manipulators (KCMs) is considered. For these robots, we show that the force component selection approach is not appropriate in general to solve the force control problem. Moreover, by formulating the problem in the joint space, we show how to properly design a stable force controller for KCMs subject to arbitrary external forces applied to their end-effector. Experimental results with a kinematically constrained laparoscopic comanipulator illustrate these propositions