Technical session talks from ICRA 2012
TechTalks from event: Technical session talks from ICRA 2012
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Soft Tissue Interaction
Novel Indentation Depth Measuring System for Stiffness Characterization in Soft Tissue PalpationThis paper presents a novel approach to measuring the indentation depth of a stiffness sensor in real time during a soft tissue palpation activity. The proposed system is integrated into a stiffness probe and is designed to intra-operatively aid the surgeon to rapidly identify the tissue abnormalities with minimum measurement inaccuracies due to tissue surface profile variations. Stiffness probe and the associated surface profile sensors are pneumatic and the newly designed system can concurrently measure the indentation depth and surface profile variations while sliding over the soft tissues in any direction in a near frictionless manner. With the pneumatic pressure maintained constant, the displacement of the sensing element is a direct function of the stiffness of the tissue under investigation. The sensor has a tunable force range and the indentation force can be adjusted externally to match tissue limitations. The prototype of the new design of stiffness probe was calibrated and tested on silicone blocks simulating soft tissue. The results show that this sensor can measure indentation depth more accurately than air cushion probe alone. The structure, working principle, and a mathematical model for this new design are described.
Robotic Compression of Soft TissueThis paper investigates automation of soft tissue compression for robot-assisted surgery. This is a fundamental task in surgery and includes interaction with a variety of tissues with unknown properties. In addition, due to sterilization and size constraints the use of contact force and position sensors are often avoided in surgical applications. We propose an Adaptive Model Predictive Control approach for execution of given tool trajectories in contact with unknown tissues in the absence of contact measurements. The Unscented Kalman Filter is employed in advance of system operation to identify the dynamics of a cable driven manipulator. These dynamics are then used to estimate contact force and position in free motion and in contact with tissue. An optimal control problem for automating tissue compression is formulated and is solved in real-time using Differential Dynamic Programming with Automatic Differentiation. The proposed methods are evaluated in experiments on an artificial tissue sample with unknown properties.
Soft Tissue Force Control Using Active Observers and Viscoelastic Interaction ModelControlling the interaction between the robot and living soft tissues has became an important issue as the number of robots inside the operating room increases. Many research works have been done in order to control this interaction. Nowadays, researches are running in force control for helping surgeons in medical procedures such as motion compensation in beating heart surgeries and tele-operation systems with haptic feedback. The viscoelasticity property of the interaction between organ tissue and robotic instrument further complicates the force control design which is much easier in other applications by assuming the interaction model to be elastic (industry, stiff object manipulation, etc.). In order to increase the performance of a model based force control, this work presents a force control scheme using Active Observer (AOB) based on a viscoelastic interaction model. The control scheme has shown to be stable through theoretical analysis and its performance was evaluated and compared with a control scheme based on a classical elastic model through experiments, showing that a more realistic model can increases the performance of the force control.
Estimation of Soft Tissue Mechanical Parameters from Robotic Manipulation DataRobotic motion planning algorithms used for task automation in robotic surgical systems rely on availability of accurate models of target soft tissue's deformation. Relying on generic tissue parameters in constructing the tissue deformation models is problematic; because, biological tissues are known to have very large (inter- and intra-subject) variability. A priori mechanical characterization (e.g., uniaxial bench test) of the target tissues before a surgical procedure is also not usually practical. In this paper, a method for estimating mechanical parameters of soft tissue from sensory data collected during robotic surgical manipulation is presented. The method uses force data collected from a multiaxial force sensor mounted on the robotic manipulator, and tissue deformation data collected from a stereo camera system. The tissue parameters are then estimated using an inverse finite element method. The effects of measurement and modeling uncertainties on the proposed method are analyzed in simulation. The results of experimental evaluation of the method are also presented.
Modeling of Needle-Tissue Interaction Forces During Surgical SuturingThis paper presents a model of needle tissue interaction forces that a rigid suture needle experiences during surgical suturing. The needle-tissue interaction forces are modeled as the sum of lumped parameters. The model has three main components; friction, tissue compression, and cutting forces. The tissue compression force uses the area that the needle sweeps out during a suture to estimate both the force magnitude and force direction. The area that the needle sweeps out is a direct result of driving the needle in a way that does not follow the natural curve of the needle. The friction force is approximated as a static friction force along the shaft of the needle. The cutting force acts only on the needle tip. The resulting force and torque model is experimentally validated using a tissue phantom. These results indicate that the proposed lumped parameter model is capable of accurately modeling the forces experienced during a suture.
Modeling of a Steerable Catheter Based on Beam TheoryCatheter-based cardiac ablation is an interventional treatment for heart arrhythmias. Pull-wire steerable catheters are guided to the heart chambers through the vasculature in order to deliver energy to destroy faulty electrical pathways in the heart. The effectiveness of this treatment is dependent on the accuracy of positioning the catheter tip at the target location and also on maintaining contact with the target while the heart is beating. Therefore, it is desirable to perform hybrid force/position control of the catheter tip. We have studied the problem of modeling the distal part of a steerable catheter using beam theory and have developed and validated a static force-deflection model through extensive experiments. It is shown that the model can estimate the shape of the bending section of a catheter using force information and without requiring any knowledge of the catheterâ€™s internal structure.