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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 technique for soft tissue model parameter estimation using experimental data. The most commonly used linear mass-spring-damper models are discussed and investigated in details, extended with two more complex, yet significantly more effective modeling approaches. The transfer functions of these models are created, and the analytical response curves are fit to the experimental...
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