Heart motion compensation for robotic-assisted surgery predictive approach vs. active observer

Abstract

In beating-heart surgeries, two natural disturbances affect surgeon's skills: respiration and heartbeats. Heart motions are too dynamic to be manually compensated, therefore robotic-assisted surgery has the potential to improve surgical tasks, especially those requiring high precision such as needle insertion or suturing. In our approach only force data are used to autonomously compensate physiological motions. Two force control architectures are confronted and experimentally compared, using a lightweight 7 DOF WAM arm. One is based on linear predictive control, which uses a mathematical model to predict the system behavior. The other one is based on model reference adaptive control with stochastic active observers.