Reaction force and surface deformation estimation based on heuristic tissue models

Abstract

Advanced surgical robotic systems aim to offer improved capabilities through automated low-level functions. In the applications, soft tissue mechanics and tool-tissue interaction modeling play an important role in achieving optimal control, relying on model-based control methods. This approach allows for addressing crucial issues during teleoperation, such as time-delay, state observation or stability. This paper presents a novel approach for modeling the behavior of soft tissue during surgical interventions, relying on the widely-employed concept of rheological models. The nonlinear Wiecher model is used for reaction force estimation during tissue indentation, tested on beef liver samples for acquiring mechanical parameters from experimental data. Curve fitting methods were used in both stress relaxation and constant indentation speed compression phases. Reaction forces are estimated using the proposed model, followed by verification tests on ex-vivo beef liver samples. The results of this research showed that the proposed novel rheological soft tissue model is capable of estimating the reaction forces acting on the tool, if the shape of the deformed tissue is known in time. This model can be successfully integrated into closed-loop surgical robot controllers.