LWPR-model based predictive force control for serial comanipulation in beating heart surgery

Robotic assistance to beating heart surgery requires high performance cardiac motion compensation in order to provide the surgeon with enhanced precision capacity. In this paper, serial comanipulation is considered, where a surgeon handles an active instrument which is in contact with the beating heart. The surgeon's hand is in charge of low frequency motions that correspond to the surgical task while the active part of the instrument moves in synchronism with the heart motion in order to guarantee that the contact is maintained thanks to the application of a controlled force. The paper introduces a 1 DOF hand-held prototype designed for active compensation of cardiac motion by the mean of force control. It then focuses on control aspects. Here, a crucial problem occurs: there is a lack of a parametric model describing the interaction between the surgical instrument and the heart that would provide enough precision for prediction. To cope with this problem, a “black box” algorithm is used as a model. Namely, the robot low level controller and the beating heart are modeled thanks to a Locally Weighted Projection Regression (LWPR). The paper discusses how this technique can be used in the context of predictive force control and shows conclusive simulation results.