In our previous work [1], the potential benefits of Magneto-Rheological Fluid based actuators to the field of haptics were studied. Our results showed that the superior mechanical attributes of such actuators contribute to improvement of stability and transparency in haptic devices. To this end, a novel design of a small-scale MRF-based clutch, was proposed in [1]. This paper reports on the development and validation of the proposed MRF-based clutch. In addition, a closed-loop torque control strategy is presented. The feedback signal used in this control scheme comes from the magnetic field measurement and is used to compensate for the nonlinear behavior using an estimated model, based on Artificial Neural Networks (ANNs). Such a control strategy eliminates the need for torque sensors for providing feedback signals. The performance of the developed design and the effectiveness of the proposed modeling and control techniques are experimentally validated. The results clearly demonstrate that the clutch shows great potential for use in a multiple degrees-of-freedom (DOF) haptic interface for a class of medical applications.

This paper reports on the performance evaluation of Magneto-Rheological Fluid (MRF) based actuation systems when used in haptic interfaces. MRF-based actuators exhibit superior characteristics, which can significantly contribute to the transparency and stability of haptic devices. To validate this statement, a prototype two degrees-of-freedom (DoF) haptic interface is constructed. A distributed antagonistic configuration is used in order to develop the 2-DoF haptic interface based on small-scale MRF-based clutches for a class of medical applications. The developed device is compared with three conventional haptic interfaces and their stability is compared using the Virtual Wall experiment. Next, the prototype interface is incorporated in a master-slave teleoperation medical setup. Preliminary studies on the performance of the haptic interface show great potential of MRF-based actuators for integration in haptic devices for medical interventions that require safe, accurate, and stable force representation.

Concentric-tube robots can offer a suitable compromise between force and curvature control. In a previous study by the authors, a real-time trajectory tracking scheme for an unloaded concentric-tube robot was developed. One of the practical barriers to the use of a concentric-tube robot in medical applications is compensation for the impact of environmental forces which can cause drastic deterioration in tracking performance. In this paper, by modifying the robot's forward kinematics and Jacobian, a new method is developed to facilitate tip tracking in real-time while accounting for an external load at the robot's tip. By considering the tip deflection resulting from the external load, a novel dual-layer control architecture is proposed to compensate for this deflection during trajectory tracking. In order to measure the force exerted on the tip position of the robot, a new technique is proposed that can move the sensing system from the distal tip to the proximal base. Experimental results are given to illustrate the effectiveness of the proposed method.

Concentric-tube robots can offer dexterous positioning even in a small constrained environment. This technology turns out to be beneficial in many classes of minimally invasive procedures. However, one of the barriers to the practical use of a concentric-tube robot is the design of a real-time control scheme. In previous work by the authors, a computationally efficient torsionally compliant kinematic model of a concentric-tube robot was developed. Using this computationally fast technique and deriving the robot's Jacobian, a new position control approach is proposed in this paper. This mechanism provides computational efficiency as well as good tracking accuracy. To evaluate the performance, experiments were conducted, and the results obtained demonstrate the feasibility of enabling the robot's tip to perform trajectory tracking in real time.

In this paper, a vibration-assisted needle insertion technique has been proposed in order to reduce needle-tissue friction. The LuGre friction model was employed as a basis for the current study and the model was extended and analyzed to include the impact of high-frequency vibration on translational friction. Experiments were conducted to evaluate the role of insertion speed as well as vibration frequency on frictional effects. In the experiments conducted, an 18 GA brachytherapy needle was vibrated and inserted into an ex-vivo soft tissue sample using a pair of amplified piezoelectric actuators. Analysis demonstrates that the translational friction can be reduced by introducing a vibratory low-amplitude motion onto a regular insertion profile, which is usually performed at a constant rate.

This paper presents a new approach to account for distributed friction in needle insertion in soft tissue. As is well known, friction is a complex nonlinear phenomenon, and it appears that classical or static models are unable to capture some of the observations in systems subject to significant frictional effects. To characterize dynamic features when the needle is very flexible and friction plays an important role in bending mechanics or when a stop-and-start planning scenario is implemented at low insertion velocities, a distributed LuGre model can be adopted. Experimental results using an artificial phantom illustrate that the proposed method is capable of representing the main features of friction which is a major force component in needle-tissue interaction during percutaneous interventions.

This paper presents a new needle deflection model that is an extension of prior work in our group based on the principles of beam theory. The use of a long flexible needle in percutaneous interventions necessitates accurate modeling of the generated curved trajectory when the needle interacts with soft tissue. Finding a feasible model is important in simulators with applications in training novice clinicians or in path planners used for needle guidance. Using intra-operative force measurements at the needle base, our approach relates mechanical and geometric properties of needle-tissue interaction to the net amount of deflection and estimates the needle curvature. To this end, tissue resistance is modeled by introducing virtual springs along the needle shaft, and the impact of needle-tissue friction is considered by adding a moving distributed external force to the bending equations. Cutting force is also incorporated by finding its equivalent sub-boundary conditions. Subsequently, the closed-from solution of the partial differential equations governing the planar deflection is obtained using Green's functions. To evaluate the performance of our model, experiments were carried out on artificial phantoms.