Neural network enhanced robot tool identification and calibration for bilateral teleoperation

© 2013 IEEE. In teleoperated surgery, the transmission of force feedback from the remote environment to the surgeon at the local site requires the availability of reliable force information in the system. In general, a force sensor is mounted between the slave end-effector and the tool for measuring the interaction forces generated at the remote sites. Such as the acquired force value includes not only the interaction force but also the tool gravity. This paper presents a neural network (NN) enhanced robot tool identification and calibration for bilateral teleoperation. The goal of this experimental study is to implement and validate two different techniques for tool gravity identification using Curve Fitting (CF) and Artificial Neural Networks (ANNs), separately. After tool identification, calibration of multi-axis force sensor based on Singular Value Decomposition (SVD) approach is introduced for alignment of the forces acquired from the force sensor and acquired from the robot. Finally, a bilateral teleoperation experiment is demonstrated using a serial robot (LWR4+, KUKA, Germany) and a haptic manipulator (SIGMA 7, Force Dimension, Switzerland). Results demonstrated that the calibration of the force sensor after identifying tool gravity component by using ANN shows promising performance than using CF. Additionally, the transparency of the system was demonstrated using the force and position tracking between the master and slave manipulators

Teleoperation of MRI-Compatible Robots with Hybrid Actuation and Haptic Feedback

Image guided surgery (IGS), which has been developing fast recently, benefits significantly from the superior accuracy of robots and magnetic resonance imaging (MRI) which is a great soft tissue imaging modality. Teleoperation is especially desired in the MRI because of the highly constrained space inside the closed-bore MRI and the lack of haptic feedback with the fully autonomous robotic systems. It also very well maintains the human in the loop that significantly enhances safety. This dissertation describes the development of teleoperation approaches and implementation on an example system for MRI with details of different key components. The dissertation firstly describes the general teleoperation architecture with modular software and hardware components. The MRI-compatible robot controller, driving technology as well as the robot navigation and control software are introduced. As a crucial step to determine the robot location inside the MRI, two methods of registration and tracking are discussed. The first method utilizes the existing Z shaped fiducial frame design but with a newly developed multi-image registration method which has higher accuracy with a smaller fiducial frame. The second method is a new fiducial design with a cylindrical shaped frame which is especially suitable for registration and tracking for needles. Alongside, a single-image based algorithm is developed to not only reach higher accuracy but also run faster. In addition, performance enhanced fiducial frame is also studied by integrating self-resonant coils. A surgical master-slave teleoperation system for the application of percutaneous interventional procedures under continuous MRI guidance is presented. The slave robot is a piezoelectric-actuated needle insertion robot with fiber optic force sensor integrated. The master robot is a pneumatic-driven haptic device which not only controls the position of the slave robot, but also renders the force associated with needle placement interventions to the surgeon. Both of master and slave robots mechanical design, kinematics, force sensing and feedback technologies are discussed. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. MRI compatibility is evaluated extensively. Teleoperated needle steering is also demonstrated under live MR imaging. A control system of a clinical grade MRI-compatible parallel 4-DOF surgical manipulator for minimally invasive in-bore prostate percutaneous interventions through the patient’s perineum is discussed in the end. The proposed manipulator takes advantage of four sliders actuated by piezoelectric motors and incremental rotary encoders, which are compatible with the MRI environment. Two generations of optical limit switches are designed to provide better safety features for real clinical use. The performance of both generations of the limit switch is tested. MRI guided accuracy and MRI-compatibility of whole robotic system is also evaluated. Two clinical prostate biopsy cases have been conducted with this assistive robot

A Sensorized Instrument for Minimally Invasive Surgery for the Measurement of Forces during Training and Surgery: Development and Applications

The reduced access conditions present in Minimally Invasive Surgery (MIS) affect the feel of interaction forces between the instruments and the tissue being treated. This loss of haptic information compromises the safety of the procedure and must be overcome through training. Haptics in MIS is the subject of extensive research, focused on establishing force feedback mechanisms and developing appropriate sensors. This latter task is complicated by the need to place the sensors as close as possible to the instrument tip, as the measurement of forces outside of the patient\u27s body does not represent the true tool--tissue interaction. Many force sensors have been proposed, but none are yet available for surgery. The objectives of this thesis were to develop a set of instruments capable of measuring tool--tissue force information in MIS, and to evaluate the usefulness of force information during surgery and for training and skills assessment. To address these objectives, a set of laparoscopic instruments was developed that can measure instrument position and tool--tissue interaction forces in multiple degrees of freedom. Different design iterations and the work performed towards the development of a sterilizable instrument are presented. Several experiments were performed using these instruments to establish the usefulness of force information in surgery and training. The results showed that the combination of force and position information can be used in the development of realistic tissue models or haptic interfaces specifically designed for MIS. This information is also valuable in order to create tactile maps to assist in the identification of areas of different stiffness. The real-time measurement of forces allows visual force feedback to be presented to the surgeon. When applied to training scenarios, the results show that experience level correlates better with force-based metrics than those currently used in training simulators. The proposed metrics can be automatically computed, are completely objective, and measure important aspects of performance. The primary contribution of this thesis is the design and development of highly versatile instruments capable of measuring force and position during surgery. A second contribution establishes the importance and usefulness of force data during skills assessment, training and surgery

Realistic tool-tissue interaction models for surgical simulation and planning

Surgical simulators present a safe and potentially effective method for surgical training, and can also be used in pre- and intra-operative surgical planning. Realistic modeling of medical interventions involving tool-tissue interactions has been considered to be a key requirement in the development of high-fidelity simulators and planners. The soft-tissue constitutive laws, organ geometry and boundary conditions imposed by the connective tissues surrounding the organ, and the shape of the surgical tool interacting with the organ are some of the factors that govern the accuracy of medical intervention planning.\ud \ud This thesis is divided into three parts. First, we compare the accuracy of linear and nonlinear constitutive laws for tissue. An important consequence of nonlinear models is the Poynting effect, in which shearing of tissue results in normal force; this effect is not seen in a linear elastic model. The magnitude of the normal force for myocardial tissue is shown to be larger than the human contact force discrimination threshold. Further, in order to investigate and quantify the role of the Poynting effect on material discrimination, we perform a multidimensional scaling study. Second, we consider the effects of organ geometry and boundary constraints in needle path planning. Using medical images and tissue mechanical properties, we develop a model of the prostate and surrounding organs. We show that, for needle procedures such as biopsy or brachytherapy, organ geometry and boundary constraints have more impact on target motion than tissue material parameters. Finally, we investigate the effects surgical tool shape on the accuracy of medical intervention planning. We consider the specific case of robotic needle steering, in which asymmetry of a bevel-tip needle results in the needle naturally bending when it is inserted into soft tissue. We present an analytical and finite element (FE) model for the loads developed at the bevel tip during needle-tissue interaction. The analytical model explains trends observed in the experiments. We incorporated physical parameters (rupture toughness and nonlinear material elasticity) into the FE model that included both contact and cohesive zone models to simulate tissue cleavage. The model shows that the tip forces are sensitive to the rupture toughness. In order to model the mechanics of deflection of the needle, we use an energy-based formulation that incorporates tissue-specific parameters such as rupture toughness, nonlinear material elasticity, and interaction stiffness, and needle geometric and material properties. Simulation results follow similar trends (deflection and radius of curvature) to those observed in macroscopic experimental studies of a robot-driven needle interacting with gels