Intracardiac transcatheter systems guided by advanced imaging modalities are gaining popularity in treating mitral regurgitation in non-surgical candidates. Robotically steerable transcatheter systems must use model-based control strategies to ensure safer and more effective transcatheter procedures with less trauma while using smaller control gains. In this paper, a 4-DoF robotically steerable tendon-driven robot was fabricated, and the relationship between the tendon displacement and the joint angle was derived. This relation was derived in two parts to make this approach applicable to any other catheter system. A model was derived to determine the tendon tensions needed to achieve desired joint angles. Then, the tendon characteristics were studied, and a tendon elongation (TE) model was derived as a function of tendon length. Executing the modeling process in two steps makes it easy to introduce additional parameters like length, friction, and pose, to characterize complex systems like catheters. The TE model was used to actuate the joints of the robot and RMSE was computed to characterize its performance. Also, PID control was used along with the TE model to improve the system's performance, and the contribution of the model and the controller in the system was recorded.

Peripheral vascular intervention remains a challenging procedure mainly due to the tortuosity of the vessels needing to be traversed by guidewires and catheters. In addition, handling long guidewires while navigating tortuous vasculature requires extensive time and skill from the surgeon. In this work, a compact guidewire advancement mechanism is proposed that is able to dispense guidewires up to 150 cm in length. The mechanism is adapted to actuate a prototype of the modified COaxially Aligned STeerable (COAST) guidewire robot to perform follow-the-leader (FTL) motion. The design of this mechanism consists of a spool, with actuation components nested inside to vary the bending length, actuate the tendon, and deflect the tip of the guidewire. The spool is mounted onto a lead screw that dispenses the guidewire with a tolerance of ±2mm. A modified bending joint kinematics and statics model is developed to characterize and validate the relationship between the tendon stroke and the desired curvature. The model is further used in a control system to navigate the distal tip through an ex vivo porcine aorta.

Magnetic resonance imaging (MRI) can provide high-quality 3-D visualization of target anatomy, surrounding tissue, and instrumentation, but there are significant challenges in harnessing it for effectively guiding interventional procedures. Challenges include the strong static magnetic field, rapidly switching magnetic field gradients, high-power radio frequency pulses, sensitivity to electrical noise, and constrained space to operate within the bore of the scanner. MRI has a number of advantages over other medical imaging modalities, including no ionizing radiation, excellent soft-tissue contrast that allows for visualization of tumors and other features that are not readily visible by other modalities, true 3-D imaging capabilities, including the ability to image arbitrary scan plane geometry or perform volumetric imaging, and capability for multimodality sensing, including diffusion, dynamic contrast, blood flow, blood oxygenation, temperature, and tracking of biomarkers. The use of robotic assistants within the MRI bore, alongside the patient during imaging, enables intraoperative MR imaging (iMRI) to guide a surgical intervention in a closed-loop fashion that can include tracking of tissue deformation and target motion, localization of instrumentation, and monitoring of therapy delivery. With the ever-expanding clinical use of MRI, MRI-compatible robotic systems have been heralded as a new approach to assist interventional procedures to allow physicians to treat patients more accurately and effectively. Deploying robotic systems inside the bore synergizes the visual capability of MRI and the manipulation capability of robotic assistance, resulting in a closed-loop surgery architecture. This article details the challenges and history of robotic systems intended to operate in an MRI environment and outlines promising clinical applications and associated state-of-the-art MRI-compatible robotic systems and technology for making this possible.

This paper presents the mechanism and design of a robotically steerable catheter system for percutaneous and minimally invasive treatment of mitral regurgitation. One of the main causes of mitral regurgitation is an impaired mitral valve topology, that results in severe heart-related diseases. Repair or replacement of the mitral valve through open-heart surgery such as traditional sternotomy has been conducted as a treatment. However, at least 50 % of patients with severe mitral regurgitation are not candidates for this surgery due to their age or comorbidities. Recently, minimally invasive or transcatheter approaches for mitral valve repair/replacement have been gaining attention to minimize the surgery's risk and several catheter mechanisms have been proposed in early phase clinical trials. Although dexterity and manipulability are essential functions in the transcatheter procedure, a direct torsional capability has not been implemented in the systems. We present a design of a 5-DoF robotically steerable catheter having two bending joints, two torsion joints having a direct torquing design, and a mitral implant delivery module to provide dexterous manipulation of the tip of the catheter. Designs and kinematic models of each joint module are presented and their performance is verified with experiments. Lastly, a mitral clip implanting procedure is demonstrated in a phantom heart model.

Cervical spinal cord injury (SCI) can severely impact hand motor and sensory function, and accordingly, patients with SCI are often unable to complete basic everyday tasks without assistance. In recent years, there has been an increase in hand exoskeleton research due to their distinct advantages for improving rehabilitation. In this work, we present a voice-controlled, tendon-driven soft robotic hand rehabilitation exoskeleton for hand function improvement in patients with cervical SCI. A new fabrication process utilizing high consistency rubber silicone is used to construct a formfitting, durable, and customizable exoskeleton glove. Bioinspired tendon routing pathways embedded within the glove create 5 actively actuated degrees-of-freedom in the index finger, middle finger, and thumb for both extension and flexion. Tendon tension sensors are developed and integrated into the exoskeleton system. The force feedback from the sensors is used in the implementation of admittance control for the exoskeleton system to improve grasping motions. The exoskeleton was evaluated in a case study with a healthy participant through range-of-motion characterization, pinch force testing, admittance controller validation, and object manipulation.

This article introduces the analysis and control of a meso-scale two degree-of-freedom robotic endoscopic tool body for minimally invasive surgeries. The design of the robotic tool uses two types of a tendon-driven joint known as a bending flexure joint that allows us to control each degree-of-freedom by minimizing interjoint coupling by design. Pure kinematic modeling and control for these robots may not provide precise control performance due to kinematic uncertainties arising from tendon elongation, tendon slacking, gear backlash, etc. We propose a static model for each of the joints of the robotic tool that avoids several of these problems. Depending on the direction of tendon tension application, the proximal joint displays considerable hysteresis due to the superelastic material characteristics and this is included in our static model. The statics of a highly compliant distal joint is also modeled and validated using finite element analysis and experimental data. Using these models, we develop a control system that comprises of a disturbance observer and the proposed static model to provide precise force control and compensate for joint hysteresis.

Mitral regurgitation is one of the most common heart diseases caused by ventricular dysfunction or anatomic abnormality of the mitral valve. The fundamental treatment for mitral regurgitation is to repair/replace the mitral valve through open-heart surgery which is risky and requires more time to recover or through minimally invasive approaches, which have significant challenges and limitations. Through the transcatheter approach, the mitral valve implant is minimally invasively delivered directly to the mitral valve and is clamped onto the leaflet to mitigate or prevent regurgitation. However, this procedure requires delicate manipulation of the catheter in a constrained space and remains a challenging problem. In this work, we present a robotically steerable cathether design for the transcatheter procedure to address mitral regurgitation. The proposed catheter consists of two bending joints, one torsion joint, and implant delivery module at the distal end of the robot. Kinematic models for each joint design are derived and compared with experimental results. Finally, we experimentally demonstrate the feasibility of the proposed catheter to navigate in a phantom heart model. In this demonstration, the bending joint was actuated by 75°, the torsion joint was actuated by 90° and the implant was pushed out by 1.8 mm to deliver the implant.

This paper presents the development of a fiber Bragg grating (FBG) bending sensor for shape memory alloy (SMA) bending modules. Due to the small form factor, low cost, and large-deflection capability, SMA bending modules can be used to construct disposable surgical robots for a variety of minimally invasive procedures. To realize a closed-loop control of SMA bending modules, an intrinsic bending sensor is imperative. Due to the lack of bending sensors for SMA bending modules, we have developed an FBG bending sensor by integrating FBG fibers with a superelastic substrate using flexible adhesive. Since the substrate is ultra-thin and adhesive is flexible, the sensor has low stiffness and can measure large curvatures. Additionally, due to the orthogonal arrangement of the sensor/actuator assembly, the influence of temperature variation caused by SMA actuation can be compensated. The working principle of the developed sensor was modeled followed by simulations. After experimentally evaluating the developed model, the sensor was integrated with an SMA bending module and cyclically bi-directionally deflected. The experimental results proved the relatively high measurement accuracy, high repeatability, and large measurable curvatures of the sensor, although hysteresis was observed due to friction.

Hydrocephalus in the pediatric population is often treated with endoscopic procedures, in which a rigid endoscope provides a working channel and needed visualization for brain manipulation. The lack of flexible and steerable endoscopic tools limits the ability of the surgeon to conduct complex operations. In this paper, we propose the design of a novel tool for such procedures that uses the compliance of a bending flexural joint to build a compact steerable multi-joint tool. These joints are machined into a tube made of a super-elastic material to create two joints near the tip of the tool. The directional stiffness properties of the flexural joint are exploited to minimize inter-joint coupling. We perform a static analysis of each joint and a kinematic analysis of the entire robot. We follow this with the design of a hand-held controller for this robot, and analyze its ability to control multiple degrees-of-freedom of the robot while minimizing the coupling between joints.

In this work, we propose a voice-controlled hand rehabilitation device driven by exotendons. A smartphone-based voice recognition system interprets user intention and is utilized for various grasping tasks. A bio-inspired tendon routing mechanism provides four-degrees-of-freedom (DoFs) across the thumb, index finger, and middle finger. A novel thumb sleeve design is presented for stable thumb movement. The exoskeleton is fabricated from polyurethane rubber and rigid 3D-printed parts to provide form-fitting properties while constraining tendon motion. Twisted string actuators and spring units provide active flexion and passive extension, respectively. The compact nature of the actuation unit allows for placement on the forearm, improving the portability of the system. The voice control system allows for easy user manipulation and accessibility and may improve rehabilitation efficiency. The performance of the tendon routing and thumb sleeve design were experimentally evaluated and voice control system was evaluated with various grasping tests.

Robotic artificial muscles are a subset of artificial muscles that are capable of producing biologically inspired motions useful for robot systems, i.e., large power-to-weight ratios, inherent compliance, and large range of motions. These actuators, ranging from shape memory alloys to dielectric elastomers, are increasingly popular for biomimetic robots as they may operate without using complex linkage designs or other cumbersome mechanisms. Recent achievements in fabrication, modeling, and control methods have significantly contributed to their potential utilization in a wide range of applications. However, no survey paper has gone into depth regarding considerations pertaining to their selection, design, and usage in generating biomimetic motions. In this paper, we discuss important characteristics and considerations in the selection, design, and implementation of various prominent and unique robotic artificial muscles for biomimetic robots, and provide perspectives on next-generation muscle-powered robots.

In most cases of peripheral arterial disease (PAD), the operating surgeon must use a variety of catheters riding on a thin wire known as a `guidewire'. This guidewire must be manually navigated through a tortuous pathway of arteries to arrive at the diseased area. Automation of the guidewire therefore reduces surgeon effort and minimizes the time required for a PAD procedure, but is restricted by the size constraints of a standard guidewire. This work presents the design of a robotically actuated 2 degree-of-freedom (DoF) guidewire tip comprised of joints laser micro-machined into a 0.78 mm (<; 2.4 Fr) Nitinol tube. We present an analysis of the notch joint used as a building block in the robot and a control strategy for this type of a joint. The experimental results show that tendon force is an important observable quantity that can be used as a shape sensing mechanism for this type of a joint in practical control applications.

Deep intracranial tumor removal can be achieved if the neurosurgical robot has sufficient flexibility and stability. Towards achieving this goal, we have developed a spring-based continuum robot, namely a Minimally Invasive Neurosurgical Intracranial Robot (MINIR-II) with novel tendon routing and tunable stiffness for use in a magnetic resonance imaging (MRI) environment. The robot consists of a pair of springs in parallel, i.e., an inner inter-connected spring that promotes flexibility with decoupled segment motion and an outer spring that maintains its smooth curved shape during its interaction with the tissue. We propose a shape memory alloy (SMA) spring backbone that provides local stiffness control and a tendon routing configuration that enables independent segment locking. In this work, we also present a detailed local stiffness analysis of the SMA backbone and model the relationship between the resistive force at the robot tip and the tension in the tendon. We also demonstrate through experiments, the validity of our local stiffness model of the SMA backbone and the correlation between the tendon tension and the resistive force. We also performed MRI compatibility studies of the 3-segment MINIR-II robot by attaching it to a robotic platform that consists of SMA spring actuators with integrated water cooling modules.

Minimally invasive neurosurgical robotic procedure performed under real-time MRI can be achieved with a robot that is head-mounted and fits in a standard MRI bore. The design of a remotely-actuated cable-driven robotic system is presented in this work. A head mounted insertion module has been developed to advance the robot module towards the target brain tumor. The robot module is formed by snapping together a reusable part that leads to the remotely-placed actuators and a disposable part which includes the previously developed spring-based MINIR-II robot. Gear transmission mechanism was implemented in the robot module to transmit the force from the actuators to the end effectors of the robot. The robot module and the insertion module are lightweight and compact with a total weight of 250 g and a total height of 222 mm. This allows the entire setup to be placed vertically on a patient's head in a closed MRI bore. The compact design of the robot module has been achieved, significantly due to the innovative modifications made to the structure of standard spur gears and smart routing of the cables around the gears. The completely MRI-compatible Bowden cable module has been implemented to allow transmission of significant force of around 10 N required for the actuation of the robot. A static friction model has been used to estimate the friction coefficient for the Bowden cable module as a preliminary step towards the complete modeling of the entire robotic system. The relationships between the input displacement and force of the cable at the actuator end and those at the middle and end robot segments were determined through experiments and discussed. A functional robotic system has been presented with the robot being inserted into the phantom tissue and only the end segment actuated back and forth.

This paper presents the development of a skull-mounted robotic headframe for intracranial neurosurgery. The headframe is primarily comprised of a pedestal, a Stewart platform, and a linear actuation module interfacing with a mesoscale neurosurgical robot. In addition to kinematic modeling, motion planning is carried out for neurosurgical procedures using the headframe. Due to the symmetric neurosurgical robot and the insertion and retraction motion of the linear actuation module, the headframe includes kinematic redundancy and it is utilized to enhance the positioning accuracy of the system. In this paper, several simulations are conducted to evaluate the headframe workspace, followed by an experimental study of the positioning error of the neurosurgical robot and a proof-of-concept demonstration of the headframe interfacing with the neurosurgical robot.

The paper presents the use of shape memory alloy (SMA) spring actuators with real-time cooling to control the motion of the MINIR-II robot. A new actuation mechanism involving the passage of water as the cooling medium and air as the medium to drive out the water has been developed to facilitate real-time control of the springs. Control parameters, such as current, water flow rates, SMA pre-displacement, and gauge pressure of the compressed air, are identified from the SMA thermal model and from the actuation mechanism. In depth modeling and characterization have been performed regarding these parameters to optimize the robot motion speed. Forced water cooling has also been compared with forced air cooling and proved to be the superior method to achieve higher robot speed. An improved robot design and an MRI-compatible experimental platform have been developed for the implementation of the actuation mechanism.

Brain tumor, be it primary or metastatic, is usually life threatening for a person of any age. Primary surgical resection which is one of the most effective ways of treating brain tumors can have tremendously increased success rate if the appropriate imaging modality is used for complete tumor resection. Magnetic resonance imaging (MRI) is the imaging modality of choice for brain tumor imaging because of its excellent soft-tissue contrast. MRI combined with continuum soft robotics has immense potential to be the next major technological breakthrough in the field of brain cancer diagnosis and therapy. In this work, we present the design, kinematic, and force analysis of a flexible spring-based minimally invasive neurosurgical intracranial robot (MINIR-II). It is comprised of an inter-connected inner spring and an outer spring and is connected to actively cooled shape memory alloy spring actuators via tendon driven mechanism. Our robot has three serially connected 2-DoF segments which can be independently controlled due to the central tendon routing configuration. The kinematic and force analysis of the robot and the independent segment control were verified by experiments. Robot motion under forced cooling of SMA springs was evaluated as well as the MRI compatibility of the robot and its motion capability in brainlike gelatin environment.

This paper presents the design, modeling, and control of a meso-scale torsion actuator based on shape memory alloy (SMA) for image-guided surgical procedures. Developing a miniature torsion actuator is challenging, but it opens the possibility of significantly enhancing the robot agility and maneuverability. The proposed torsion actuator is bi-directionally actuated by a pair of antagonistic SMA torsion springs through alternate Joule heating and natural cooling. The torsion actuator is integrated into a surgical robot prototype to demonstrate its working performance in the humid environment under C-Arm CT image guidance.

This paper addresses the challenge of versatile aerial grasping utilizing suction while considering the limitations of an on-board vacuum pump. It builds upon our patented self-sealing suction cup technology, which allows the exertion of local pulling contact forces for grasping a wide range of objects. The novel self-sealing nature of the cups enables the gripper to be versatile, employing just one, several, or all of the cups for the grasp in a passively actuated manner. We begin by describing the design of the system and its components. Because aerial applications are typically sensitive to weight constraints, we used a micro-pump vacuum generator, which introduced new challenges for our system. To investigate and overcome those challenges, we tested the relationship between the cup's design and its leakage, activation force, and maximum holding force. In addition, we tested the performance of the individual gripper components, the aerial vehicle's ability to transfer force to the cups, the system's ability to grip inclined surfaces, and finally the vehicle's ability to grasp a multitude of objects using various numbers of cups. This included the grasping of one object, followed by the grasping of a second object while still holding the first object.

Robotic surgery, especially in the field of neurosurgery, can be tremendously improved with the integration of an excellent imaging modality during the procedure. Shape memory alloy (SMA), a high power density and inexpensive MRI-compatible actuator, is therefore being considered as an appropriate actuator for the robot. However, the low control bandwidth of SMA due to the long cooling time makes it undesirable for commercial use. An efficient and low-cost cooling method using water as a coolant that passes through a flexible tube coiled around the SMA spring is proposed to increase the cooling rate of SMA, thereby improving its actuation frequency. SMA constitutive model and heat transfer model have been developed to simulate theoretical behavior of SMA springs in antagonistic configuration. The maximum bandwidth we achieved was 0.333 Hz for tracking of a sinusoidal trajectory of 3 mm peak-to-peak magnitude. We also demonstrated the capability of our cooling system to control the motion of an SMA spring actuated one-DOF MINIR-II robot prototype.

Micro manipulation is essential for tissue indentation tasks in micro-scale experiment, and microscopes must be equipped with multi degree-of-freedom (DOF) stages to accurately reach the regions of interest (ROI). Current microscope stages have three main drawbacks when applied to material characterization tasks. First, most microscope stages are designed for 2- or 3-DOF manipulation, lacking the ability to rotate the specimen. Second, the average micro-positioning stage is manually adjusted, and finally most stages accomplish either a large travel range or sub-micron resolution manipulation, but not both. These limitations pose a challenge for phenotyping diseases using quantitative mechanical signatures. This research is motivated by the need for improved accuracy in breast cancer detection. The following work aims to improve upon current micro-positioning stages by allowing for 4-DOF motion (XYθ for in-plane motion and Z direction indentation) and the ability to employ a variety of devices for material characterization. The ability to rotate the specimen will provide improved accuracy in reaching the ROI and robust measurement in uncertain specimen environments. The work described herein explains the design and analysis toward an under-actuated micro-positioning stage for automated tissue indentation.

Brain tumor, be it primary or metastatic, is usually life threatening for a person at any age. The risks involved in carrying out surgery within a brain can cause severe anxiety in patients. However, primary surgical resection which is one of the most effective ways of treating brain tumors can have a tremendously increased success rate if the appropriate imaging modality is used for complete tumor resection. Magnetic resonance imaging (MRI) is the imaging modality of choice for brain tumor imaging because of its excellent soft-tissue contrast. MRI combined with continuum soft robotics has immense potential to be the next major technological breakthrough in the field of brain cancer diagnosis and therapy. In this work, we present the design and kinematic analysis of a flexible spring-based minimally invasive neurosurgical intracranial robot (MINIR-II). It is comprised of an inter-connected inner spring and an outer spring to enable motion in three dimensions (3D). Our design provides improved dexterity with higher degrees of freedom (DoFs) and independent joint control because of the centrally routed tendon configuration. Since the robot itself is made of plastic (except the electrocautery probes and SMA spring actuators), it is MRI-compatible and allows surgeons to track the real-time location of the robot in the brain and to reach the brain tumor target. The inter-connected spring and the outer spring are manufactured individually in a single piece using rapid prototyping technology at low cost to make it disposable after single use. Our three-segment robot has two DoFs at each segment with both joints controlled by two pairs of MRI-compatible SMA spring actuators. We also present a detailed kinematic analysis of the robot, simulation of the robot motion, and experimental evaluation of the robot motion using vision feedback.

This paper presents a prototype of a meso-scale medical robot for Neurosurgical Intracerebral Hemorrhage Evacuation (NICHE). We use shape memory alloy (SMA) actuators for actuating individual degrees-of-freedom (DoFs). Pairs of antagonistic SMA wires enable bidirectional motion of bending joints. A novel torsion joint formed by a pair of antagonistic SMA torsion springs is installed at the distal end together with a pair of antagonistic SMA wires. This design provides articulation within the hemorrhage at the robot tip, thereby enabling effective hemorrhage evacuation. In this paper we derive the forward kinematics of the robot and the constitutive model of the SMA-actuated torsion joint. We also present experimental procedures to characterize parameters of the constitutive model. Finally, a proof-of-concept experiment is presented to show the working of the robot.

This paper presents our work on design, modeling, and control of a meso-scale shape memory alloy (SMA) actuated torsion actuator for miniature robots. This novel torsion actuator is bi-directionally activated by a pair of antagonistic SMA torsion springs through alternate Joule heating. First, we present the mechanical design and fabrication approach of this miniature actuator. Then, we present the torsion spring mechanical model, SMA constitutive model, and kinematic and dynamic models, followed by the derivation of the quasi-static model of the actuator. Finally, the dynamic properties are tested by step response and sinusoidal tracking tests. A model-based controller is designed and its performance is evaluated by experiments.

Discretely actuated steerable cannula is a multi-degree-of-freedom hollow needle (cannula) that could potentially be used in needle-based procedures to deliver therapeutic and diagnostic tools to a target region through its hollow inner core. Needle-based procedures are commonly performed using intra-operative image guidance. 2D ultrasound is one of the most commonly used imaging modalities in clinics. It is portable, inexpensive and free of ionizing radiation. The success of the needle-based procedures depends on accurate detection of the needle. The accuracy of the out-of-plane detection, where the ultrasound transducer is placed at a right angle to the long-axis of the needle, depends on the ultrasound beam width. Finite width of the ultrasound beam and uniform cross-section of the needle introduce errors in tracking. The accuracy of in-plane tracking depends on the tracking algorithm used and the spatial resolution of the ultrasound transducer. This work presents a method to quantify the finite ultrasound beam width and the spatial accuracy of the transducer. An out-of-plane detection method was implemented to locate the tip of the discretely actuated steerable cannula. An in-plane tracking algorithm based on optical flow was also developed to obtain the shape of a planar cannula. The algorithms and the methods developed in this work are general and they can be extended to needles having straight, curved and arbitrary shapes.

In this paper, we model and characterize the thermomechanical behavior of SMA springs based on Brinson's constitutive model of SMAs. The model developed in this paper can be used to compute the recovery length of SMA springs. We used the model to develop a temperature feedback position controller to control the joint motion of the SMA spring-actuated robot. We also implemented a position controller for the robot using image feedback because the robot was designed to be operated under MRI guidance. Since the image tracking algorithm for image feedback control may fail in some situations, the temperature feedback controller can be used as a backup control scheme for the robot. The experimental results showed that the image feedback controller worked well while the temperature feedback controller did not. This is because the theoretical model did not include the nonlinear characteristics of the tendon-sheath mechanisms. Therefore, we used an empirical model to implement a temperature feedback controller and it was used to control the robot precisely.

Human breast tissue is by nature heterogeneous, and in the samples we studied, epithelial tissue is formed by groups of functional breast epithelial cells that are surrounded by stromal tissue in a complex intertwined way. Therefore sampling a specific cell type on an unstained specimen is very difficult. To aid us, we use digital stained images of the same tissue annotated by a certified pathologist to identify the region of interest (ROI) at a coarse magnification and an image-guided positioning system to place the unstained tissue near the AFM probe tip. Using our setup, we could considerably reduce AFM operating time and we believe that our setup is a viable supplement to commercial AFM stages with limited X-Y range.

Several percutaneous needle-based and intravascular procedures require guidance of the diagnostic or therapeutic tool to the target location by maneuvering the needle or catheter to correct for the error in reaching the target location. Hence, in this paper we present our work towards developing a discretely actuated steerable needle/cannula with multiple degrees-of-freedom to `steer' the cannula by discrete actuation along the cannula length. We are interested in using the cannula to introduce both diagnostic and therapeutic tools, which may otherwise be difficult to deliver to the appropriate location. We use two antagonistic SMA wires as actuators to generate the required bending forces at each joint. SMA wires were annealed through a customized training process to an arc shape and mounted in the machined grooves on the outer surface of the cannula to generate local bending upon thermal actuation. We propose to use temperature feedback to control the position of the SMA actuators. To use temperature feedback as the feedback signal for enabling individual joint actuation, we had to fully characterize the SMA actuator. Classical uniaxial testing devices and experimental setup used in characterizing straight annealed SMA wires are not applicable in this work since the SMA wire is annealed in an arbitrary shape. Hence, we also present an experimental setup and a procedure for characterizing an SMA actuator that transforms into an arc shape upon thermal actuation.

In this paper, we present the design and development of a magnetic resonance imaging (MRI)-compatible tendon-driven robot to overcome the limitations of our previous minimally invasive neurosurgical intracranaial robot (MINIR). In this prototype, the robot is made of plastic and the MRI-compatible shape memory alloy (SMA) actuators are placed away from the robot. The robot has four revolute joints which are placed orthogonally to have out-of-plane motion capability. Each joint is connected to a pair of antagonistic SMA spring actuators through the tendon-sheath mechanism. Each SMA spring actuator can be controlled independently to actuate the corresponding joint. A theoretical model and experimental setup have been developed to evaluate the recovery force of the SMA spring at different displacement and temperatures. The experimental results closely match the theoretical model and it shows significant promise for future development in this area. A series of MRI compatibility tests have also been performed to evaluate the MRI compatibility of the device and to assess the degradation in image quality, if any, during actuation. The experimental results clearly demonstrate that the robot is MRI-compatible and it creates no significant distortion in the MR images during actuation.

Brain tumors are the most feared complications of cancer. Their treatment is challenging due to the lack of good imaging modality and the inability to remove the complete tumor. Facilitating tumor removal by accessing regions outside the "line-of-sight" will require a highly dexterous and MRI compatible robot. We present our work towards the development of a MRI-compatible neurosurgical robot. We used two antagonistic shape memory alloy (SMA) wires as actuators for each joint. Due to the size limitation of the device, we rely on temperature feedback to control the joint motion of the robot. We have developed a theoretical model based on Tanaka's model to characterize the joint motion with the change in SMA wire temperature. The results demonstrated that the SMA wire temperature can be used reliably to predict the motion of the robot. We then used a PWM scheme and switching circuit to control the temperature of multiple SMA wires. Experimental results showed that we can actuate the robot reliably and observe joint motion in a gelatin medium. MR images also showed that the robot is fully MRI-compatible and creates no significant image distortion.

We present our work towards the development of a MR image-guided SMA-actuated neurosurgical robot. We used two antagonistic SMA wires as actuators for each joint in the robot, so that each joint can be actuated independently. We also modeled and tested the force behaviour of SMA wires in the bent configuration, which can be used as a guideline for SMA actuator selection. Due to the size scale of the robot, it is impossible to have individual position sensors at each joint and hence we rely primarily on vision feedback to control the joint motion of the robot. The images used to control the robot in this paper were obtained from a camera with the goal of eventually using MR images to control the end-effector motion. We then developed a control strategy and a switching circuit to control multiple links simultaneously and independently using only one power supply. Experimental results from our current prototype of a 3-DOF robot showed that we can actuate the robot and hence observe joint motion in a gelatin slab. We also did a series of experiments inside the MRI to show that the robot is fully MRI-compatible and creates no significant image distortion in the MR images.

Magnetic Resonance Imaging (MRI) is superior to other imaging modalities such as Ultrasound and Computed Tomography and is used for both diagnostic and therapeutic procedures. However, current breast biopsy procedures based on MR images obtained apriori, use a blind targeting approach, which can be long and painful. Current approaches, due to possible patient motion, can lead to tool tip positioning errors thereby affecting diagnostic accuracy and causing significant patient discomfort, if repeated procedures are required. Hence, it is desired to develop a MRI-compatible robot for breast biopsy procedures without removing the patient from the MRI bore. This approach could potentially avoid multiple biopsy needle insertions and minimize sampling errors. Due to the working principle of MRI, material, actuation, and sensing techniques are limited as the MR images must not be affected significantly during the procedure. In addition, the limited space of the MRI bore requires the robot to be compact. This paper presents a four degrees of freedom robot with a compact parallel mechanism of which three degrees of freedom are pneumatically actuated while the needle driver mechanism is actuated by a piezo motor. Fiber-optic force sensor is also designed, developed, and mounted on the top mobile platform of the parallel mechanism to sense the needle and tissue interaction forces. Position control of the pneumatic cylinders is implemented using PI control with a modified integration term to achieve a slow and smooth motion.

Magnetic resonance imaging (MRI) has been gaining popularity over standard imaging modalities like ultrasound and CT because of its ability to provide excellent soft-tissue contrast. However, due to the working principle of MRI, a number of conventional force sensors are not compatible. One popular solution is to develop a fiber-optic force sensor. However, the measurements along the principal axes of a number of these force sensors are highly cross-coupled. One of the objectives of this paper is to minimize this coupling effect. In addition, this paper describes the design of elastic frame structures that are obtained systematically using topology optimization techniques for maximizing sensor resolution and sensor bandwidth. Through the topology optimization approach, we ensure that the frames are linked from the input to output. The elastic frame structures are then fabricated using polymers materials, such as ABS and Delrin(®), as they are ideal materials for use in MRI environment. However, the hysteresis effect seen in the displacement-load graph of plastic materials is known to affect the accuracy. Hence, this paper also proposes modeling and addressing this hysteretic effect using Prandtl-Ishlinskii play operators. Finally, experiments are conducted to evaluate the sensor's performance, as well as its compatibility in MRI under continuous imaging.

Suction cups have long been used as a means to grasp and manipulate objects. They enable active control of grasp, enhance grasp stability, and handle some objects such as large flat plates more easily than standard graspers. However, the application of suction cups to object manipulation has been confined to a relatively small, well-defined problem set. Their potential for grasping a large range of unknown objects remains relatively unexplored. This seems in part due to the complexity involved with the design and fabrication of various materials comprising the grasper as well as actuators used to enable grasping. This paper introduces the design of a suction cup that is “self-selecting.” In other words, the suction cups comprising the grasper do not exert any suction force when the cup(s) are not in contact with the object, but instead exert a suction force only when they are in physical contact with the object. Since grasping is achieved purely by passive means, the cost and weight associated with individual sensors, valves, and/or actuators are essentially eliminated. Furthermore, the design permits the use of a central vacuum pump, thereby maximizing the suction force on an object and enabling some suction on surfaces that may prohibit tight seals. This paper presents the design, analysis, fabrication, and experimental results of such a “self-selecting” suction cup array.

Magnetic resonance imaging (MRI) has been gaining popularity over standard imaging modalities like ultrasound and CT because of its ability to provide excellent soft-tissue contrast. However, due to the working principle of MRI, a number of conventional force sensors are not compatible. One popular solution is to develop a fiber-optic force sensor. However, the measurements along the principal axes of a number of these force sensors are highly cross-coupled. One of the objectives of this paper is to minimize this coupling effect. In addition, this paper describes the design of an elastic frame structure that is obtained systematically by an algorithm and not purely based on design intuition. We used a topology optimization technique, which has two major advantages: 1) aids engineers in design when given a constrained boundary, and 2) optimize the displacement amplification, which will in turn increase stiffness, bandwidth, and improve sensing resolution. To ensure that the frames are linked from the input to output, a solution for topology optimization is proposed. The sensor is then fabricated using plastic material (ABS) as it is one of the ideal material for MRI environment. However, the hysteresis effect seen in the displacement-load graph of plastic materials is known to affect the accuracy. Hence, this paper also proposes modeling and addressing this hysteretic effect using Prandtl-Ishlinskii play operators. Finally, experiments are conducted to evaluate the sensor's performance, as well as its compatibility in MRI under continuous imaging.

Comprehensive and training simulators that provide realistic visual and haptic feedback during cell indentation tasks are currently investigated. Complex cell geometry inherent to biological cells and intricate mechanical properties drive the need for precise mechanical and numerical modeling to assure accurate cell deformation and force calculations. Advances in alternative finite element formulation, such as mass-tensor approach, have reached the state where they are applicable to model soft cell deformation in real time. The geometrical characteristics and the mechanical properties for different cells are determined with AFM indentation. A real-time, haptics-enabled simulator for cell centered indentation has been developed which utilizes the atomic force microscopy data (mechanical and geometrical properties of embryonic stem cells (mESC)) to accurately replicate the indentation task and predict the cell deformation during indentation in real-time. This tool can be used as a mechanical marker to characterize the biological state of the cell. The operator is able to feel in real-time the change in the stiffness during cell deformation between fixed and live cells. A comparison study with finite element simulations using a commercial software and the experimental data demonstrate the effectiveness of the proposed physically-based model.

In order to understand and characterize the mechanical property and response of the mouse embryonic stem cells (mESC), we used an atomic force microscope (AFM) combined with a PHANToM haptic feedback device. Atomic force microscopy has rapidly become a valuable tool for quantifying the biophysical properties of single cells or a collection of cells through force measurements. We report herein the mechanical characterization of single mESC using indentation-relaxation measurements with micro-sphere AFM probes for fixed and live undifferentiated mESC. During cell indentation for both live and fixed undifferentiated cells, we provided force feedback to the user in real-time through the PHANToM haptic feedback device as the AFM tip was deforming the cell. The force was amplified for the human operator to perceive the change in force during cell indentation by the AFM cantilever. This information can be used as a mechanical marker to characterize state of the cell (live and fixed). As the interpretation of atomic force microscopy-based indentation tests is highly dependent on the use of an appropriate theoretical model of the testing configuration, various contact models are presented to predict the mechanical behavior of an individual mouse embryonic stem cells (mESC) in different states. A comparison study with finite element simulations (FEM) of spherical tip indentation demonstrates the effectiveness of our computational model to predict the mESC deformation during indentation and relaxation nanomanipulation tasks.

This paper presents an initial design and feasibility study for a 1-DOF Magnetic Resonance Imaging (MRI) compatible needle driver robot for radiofrequency ablation (RFA). This initial design and study is necessary to further understand how to improve on many of the shortcomings in the standard RFA procedure. Combining needle driving with advanced image tracking techniques could provide improved solutions to these clinical limitations. In this paper, we present a hydraulically-actuated 1-DOF needle driver robot that is capable of advancing a radiofrequency (RF) probe into tissue at controllable velocities and positions within an MRI scanner, while collecting force feedback data and maintaining all standards of MRI-compatible design. We also present a method of interfacing the robot with a PHANToM haptic feedback device controlled from outside the MRI scanning room. Experiments demonstrating the PHANToM’s ability to receive force feedback and guide the RFA tool to a tumor nodule within a phantom breast model while continuously imaging within MRI have been presented. Our haptic feedback system enabled us to detect normal vs. tumor phantom tissue in the preliminary experiments. Our experimental results demonstrate the compatibility of the entire system for operation during continuous MRI imaging.

The introduction of robot-assisted surgery into the operating room has led to significant improvements in surgical procedures. However, the lack of haptic feedback in these robotic systems using long teleoperated instruments has negatively affected the surgeon's ability to palpate tissue and diagnose it as healthy or unhealthy. This paper describes our design of a modular, automated laparoscopic grasper with tri-directional force measurement capability. The grasper can measure normal grasping forces, as well as, sideways manipulation forces during grasping and palpation tasks. Additionally, a modular design allows for easy conversion between surgical modalities (e.g., grasping, cutting, and dissecting). Calibration of the force sensors and initial testing of the prototype has shown its ability to accurately measure tool-tissue interaction forces.

Conventional methods of manipulating individual biological cells have been prevalent in the field of molecular biology. These methods do not have the ability to provide force feedback to an operator. Poor control of cell injection force is one of the primary reasons for low success rates in cell injection and transgenesis in particular. Therefore, there exists a need to incorporate force feedback into a cell injection system. We have developed a force feedback interface, which has the capability of measuring forces in the range of$\mu{\rm N}$and provide a haptic display of the cell injection forces in real time. Using this force feedback interface, we performed several human factors studies to evaluate the effect of force feedback on cell injection outcomes. We tested our system with 40 human subjects and our experimental results indicate that the subjects were able to feel the cell injection force and confirmed our research hypothesis that the use of combined vision and force feedback leads to a higher success rate in cell injection task compared to using vision feedback alone.

There is a strong need to improve the tools clinicians use for training in procedures such as prostate brachytherapy where the success rate is directly related to the clinician's level of experience. Accurate haptic feedback is needed for developing improved surgical simulators and trainers for such procedures. In prostate brachytherapy, accurate needle placement of radioactive seeds in the prostate is crucial to the success of the surgery and to the quality of life of the patient. Therefore, a trainer or simulator for this and other types of needle insertion tasks require an accurate reality-based quantification and model of the needle and soft tissue interaction. To achieve this, we utilize the X-ray images produced by a dual C-arm fluoroscope setup during a needle insertion task to obtain parameters needed for accurate modeling of soft tissue and needle interactions. The needle and implanted markers in the tissue are tracked during the insertion and withdrawal of the needle at speeds of 1.016 mm/sec, 12.7 mm/sec and 25.4 mm/sec. Both image and force data are utilized to determine important parameters such as the local effective modulus during puncture and the approximate cutting force for soft tissue samples. A finite element model was built using the data to model needle puncture of tissue

Performing a fine manipulation task on a moving surface through a teleoperated robotic system presents significant challenges to the human operator. Addressing these challenges is particularly important in robotic surgical systems, where motion of the patient can result in surgical errors that degrade the quality of the surgery. The use of motion compensation by a robot manipulator to cancel the motion of the patient would represent a significant improvement over existing techniques. The purpose of this research is to evaluate the role of force-feedback in a motion-canceling teleoperation system. We have developed an experimental system in which the roles of motion-cancellation and teleoperation have been decoupled between separate robot manipulators. Our results lead us to the conclusion that force-feedback minimizes contact forces in motion-canceling teleoperation due to: 1) minimization of the collision forces due to the initial contact with the target surface, and 2) minimizing forces due to accidental contact generated by tracking errors by taking advantage of the naturally modulated impedance of the human hand during such tasks.

The purpose of this paper is to present our results in developing a dynamic model of the Mitsubishi PA-10 robot arm for the purpose of low velocity trajectory tracking using low feedback gains. The PA-10 is ideal for precise manipulation tasks due to the backdrivability, precise positioning capabilities, and zero backlash afforded by its harmonic drive transmission (HDT). However, the compliance and oscillations inherent in harmonic drive systems, and the lack of any technical information on the internal dynamics of the transmission, make the development of an accurate dynamic model of the robot extremely challenging. The novelty of this research is therefore the development of a systematic algorithm to extract the model parameters of a harmonic drive transmission in the robot arm to facilitate model-based control. We have modeled all 7 joints of the Mitsubishi PA-10, and we have done several experiments to identify the various parameters of the harmonic drive system. We conclude with a sample trajectory tracking task which demonstrates our model-based controller for the Mitsubishi PA-10 robot arm.

Reality-based modeling of deformable tissues is critical for providing accurate haptic feedback to the surgeon in common surgical tasks such as grasping and cutting organs/tissues. In reality-based modeling, we are interested in modeling tissues as accurately as possible by determining the mechanical properties experimentally and developing a predictive model that is self consistent with the experimentally-determined properties. In this paper, we present the newly developed hardware and software to characterize the mechanical response of pig liver during (ex-vivo) cutting. The macroscopic cutting force-displacement curve shows repeating self-similar units of localized linear loading followed by sudden unloading. The sudden unloading coincides with onset of localized crack growth. This experimental data was used to determine the self-consistent local effective Young's modulus of the specimens to be used in finite element models. Results from plane-stress and plane-strain finite element analyses reveal that the magnitude of the self-consistent local effective Young's modulus varies within close bounds.

The purpose of this paper is to present our results in developing a dynamic model of the Mitsubishi PA-10 robot arm for the purpose of low velocity trajectory tracking using very low feedback gains. The novelty of this research is therefore the development of a systematic algorithm to extract the model parameters of a harmonic drive transmission in the robot arm to facilitate model-based control. We have chosen the elbow pitch joint (joint 4) of the PA-10 robot arm for estimation and modeling purposes. We have done several experiments to identify the various parameters of the harmonic drive system. We conclude with a sample trajectory tracking task whereby the feedback torque required to do trajectory tracking with and without the parameter identification of the HDT is significantly different.

The primary goal of this research is to develop effective haptic and visual servoing methods, with the eventual goal of eliminating the need for mechanical stabilizers in a coronary artery bypass graft procedure by presenting a stationary operative site to the surgeon performing the procedure using haptic and visual feedback. We present the results from our initial work in the area of tracking a deformable membrane using vision and providing haptic feedback to the user based on the vision information and the material properties of the membrane. In our first experiment, we track the deformation of a rubber membrane in real-time through stereo vision while providing haptic feedback to the user interacting with the reconstructed membrane through the PHANToM haptic device. In the second experiment, we verify the ability of our vision system to track a point on a surface undergoing a complex 3D motion.

We present the results from our work in the development of a robotic arm with minimal impedance. The development of such an arm is useful for gentle exploration of unknown objects in unstructured environments. Similar to a human, the robotic arm should minimize the contact forces in the event of unanticipated contact with unknown objects in the absence of visual feedback. To accomplish this, our strategy is to develop a good model of the robotic system so that we can use low gains which in turn will lead to low impedance and hence low contact forces in manipulation tasks in unstructured environments. The paper demonstrates how good modeling and feedforward compensation can result in low interaction forces without any external force sensing. We present experimental results to demonstrate the validity of our model and approach.

We present a novel modeling framework and control algorithms for multiple mobile manipulators cooperatively grasping and transporting an object. The planning and control tasks are decentralized, and the framework explicitly incorporates the protocols used to coordinate the robots in the team. The framework is flexible in the sense that it scales with the number of robots and controllers. Preliminary experimental results for teams of two-three robots are shown, while simulation results are used to illustrate the extensions of our approach to larger teams.

Addresses the control of a team of robots navigating in a terrain with obstacles, while maintaining a desired formation and changing formations when required using an underlying graph theoretic framework. We state and prove the mathematical results relating to multi-robot teams moving in a formation. We model each team as a triple, (g, r, /spl Hscr/), consisting of a group element, g, that describes the gross position of the lead robot, a set of shape variables, r, that describes the relative positions of robots and a control graph, /spl Hscr/ that describes the behaviors of the robots in the formation. Our framework enables the representation and enumeration of all possible control graphs, and the coordination of transitions between any two control graphs. Further, we describe an algorithm that allows the team of robots to move between any two formations, while avoiding obstacles. As the number of robots increases, the number of possible control graphs increases. However, because the control computations are decentralized, the algorithms scale with the number of robots. We present an example to illustrate the control graphs and the algorithm for transitioning. between them in the presence and absence of sensor noise.

This paper addresses the control of a team of nonholonomic mobile robots navigating in a terrain with obstacles while maintaining a desired formation and changing formations when required, using graph theory. We model the team as a triple, (g, r, H), consisting of a group element g that describes the gross position of the lead robot, a set of shape variables r that describe the relative positions of robots, and a control graph H that describes the behaviors of the robots in the formation. Our framework enables the representation and enumeration of possible control graphs and the coordination of transitions between any two formations.

Addresses the control of a team of robots navigating in a terrain with obstacles while maintaining a desired formation and changing formations when required. We model the team as a triple consisting of a group element that describes the gross motion of the team, a set of shape variables that describe the relative positions of robots, and a control graph that describes the behaviors of the robots in the formation. We assume that a lead robot is equipped with the appropriate sensors and plans the gross motion (path) for the team. This path is derived from optimal control theory. All other robots are coordinated by continuous controllers that are prescribed by the control graph. Our framework allows us to enumerate the number of control graphs and the possible transitions between them. Further, we describe an algorithm that allows the team of robots to move between any two formations, while avoiding obstacles. We illustrate the methodology with examples involving teams of 5 and 6 robots in the presence of obstacles.

We investigate feedback laws used to control multiple robots moving together in a formation. We propose a method for controlling formations that uses only local sensor-based information, in a leader-follower motion. We use methods of feedback linearization to exponentially stabilize the relative distance and orientation of the follower, and show that the zero dynamics of the system are also (asymptotically) stable. We demonstrate in simulation the use of these algorithms to control six robots moving around an obstacle. These types of control laws can be used to control arbitrarily large numbers of robots moving in very general types of formations.

We address the problem of motion planning for nonholonomic cooperating mobile robots manipulating and transporting objects while holding them in a stable grasp. We present a general approach based on the calculus of variations that allows us to obtain optimal trajectories and actuator forces/torques for any manoeuvre in the presence of obstacles. In addition, geometric constraints such as joint limits, kinematic constraints such as nonholonomic velocity constraints and dynamic constraints can be easily incorporated into the planning scheme. The application of the method is illustrated by computing motion plans for several examples.

This paper addresses the optimal control and selection of gaits in a class of nonholonomic locomotion systems that exhibit group symmetries. We study optimal gaits for the snakeboard, a representative example of this class of systems. We employ Lagrangian reduction techniques to simplify the optimal control problem, and describe a general framework and an algorithm to obtain numerical solutions to this problem. This paper represents an initial study in using optimal control techniques to study optimality of gaits and issues involving gait transitions. The general framework provided in this paper can easily be applied to other examples of biological and robotic locomotion.

This paper studies human dual arm manipulation tasks and develops a computational model that predicts the trajectories and the force distribution for the coordination of two arms moving an object between two given positions and orientations in a horizontal plane. Our ultimate goal is to understand the dynamics of dual arm coordination in order to develop better robot control algorithms. Our computational model is based on the hypothesis proposed by Uno et al. (1989) who suggest that human movements minimize the integral of the norm of the rate of change of actuator torques. We compare the experimental trajectories and force distributions with this computational model. The first important observation is that the trajectories show a significant degree of repeatability across trials and across subjects. Next, we observe that the trajectories in the sagittal and frontal plane are characterized by asymmetric features that are hard to model using such integral cost functions. Finally, we show that the internal forces play an important role in trajectory generation. While these are repeatable across trials, they vary significantly from subject to subject.

We address the motion planning for "fixtureless" material-handling with multiple manipulators on nonholonomic carts. The mobile manipulators possess the ability to manipulate and transport objects while holding them in a stable grasp. We present a general approach that allows generation of optimal trajectories and actuator inputs for any given maneuver. Constraints such as limitations on the turning radii of the mobile manipulators or bounds on their separation can be easily incorporated into the planning scheme. Numerical solutions for several maneuvers including abrupt turns, parallel parking in cluttered environments and changes in formation are computed. Finally, we present experimental results with two mobile manipulators.

This paper addresses determination of trajectories and force distribution for cooperative manipulation with two arms through optimizing an integral cost function that depends an the actuator forces. We compare the calculated trajectories with the measurements on human subjects performing planar manipulation tasks. Our findings suggest that the trajectories and forces used by humans can be predicted by minimizing the integral of the rate of change of actuator torques over the trajectory. Good match is shown for a class of manipulation tasks in which the person-to-person variability is small. The theoretical foundation for computing the optimal solutions is briefly presented and the advantages of using such schemes for robotic systems are discussed.