Stability Boundary and Design Criteria for Haptic Rendering of Virtual Walls

This paper is about haptic simulations of virtual walls, which are represented by a discrete PD-control. A normalized discrete-time transfer function is used to derive the fundamental stability boundaries for this problem. Hereby, the case of direct action and the more often case of an one sampling step delayed action are addressed. Inside the stable region the set of all parameters was determined that result in real system poles. Furthermore, three dierent design criteria are compared to nd optimum control parameters for the virtual wall. Finally, important conclusions for haptic simulations are derived

Haptics in Robot-Assisted Surgery: Challenges and Benefits

Robotic surgery is transforming the current surgical practice, not only by improving the conventional surgical methods but also by introducing innovative robot-enhanced approaches that broaden the capabilities of clinicians. Being mainly of man-machine collaborative type, surgical robots are seen as media that transfer pre- and intra-operative information to the operator and reproduce his/her motion, with appropriate filtering, scaling, or limitation, to physically interact with the patient. The field, however, is far from maturity and, more critically, is still a subject of controversy in medical communities. Limited or absent haptic feedback is reputed to be among reasons that impede further spread of surgical robots. In this paper objectives and challenges of deploying haptic technologies in surgical robotics is discussed and a systematic review is performed on works that have studied the effects of providing haptic information to the users in major branches of robotic surgery. It has been tried to encompass both classical works and the state of the art approaches, aiming at delivering a comprehensive and balanced survey both for researchers starting their work in this field and for the experts

MACHINE LEARNING AUGMENTATION MICRO-SENSORS FOR SMART DEVICE APPLICATIONS

Novel smart technologies such as wearable devices and unconventional robotics have been enabled by advancements in semiconductor technologies, which have miniaturized the sizes of transistors and sensors. These technologies promise great improvements to public health. However, current computational paradigms are ill-suited for use in novel smart technologies as they fail to meet their strict power and size requirements. In this dissertation, we present two bio-inspired colocalized sensing-and-computing schemes performed at the sensor level: continuous-time recurrent neural networks (CTRNNs) and reservoir computers (RCs). These schemes arise from the nonlinear dynamics of micro-electro-mechanical systems (MEMS), which facilitates computing, and the inherent ability of MEMS devices for sensing. Furthermore, this dissertation addresses the high-voltage requirements in electrostatically actuated MEMS devices using a passive amplification scheme. The CTRNN architecture is emulated using a network of bistable MEMS devices. This bistable behavior is shown in the pull-in, the snapthrough, and the feedback regimes, when excited around the electrical resonance frequency. In these regimes, MEMS devices exhibit key behaviors found in biological neuronal populations. When coupled, networks of MEMS are shown to be successful at classification and control tasks. Moreover, MEMS accelerometers are shown to be successful at acceleration waveform classification without the need for external processors. MEMS devices are additionally shown to perform computing by utilizing the RC architecture. Here, a delay-based RC scheme is studied, which uses one MEMS device to simulate the behavior of a large neural network through input modulation. We introduce a modulation scheme that enables colocalized sensing-and-computing by modulating the bias signal. The MEMS RC is tested to successfully perform pure computation and colocalized sensing-and-computing for both classification and regression tasks, even in noisy environments. Finally, we address the high-voltage requirements of electrostatically actuated MEMS devices by proposing a passive amplification scheme utilizing the mechanical and electrical resonances of MEMS devices simultaneously. Using this scheme, an order-of-magnitude of amplification is reported. Moreover, when only electrical resonance is used, we show that the MEMS device exhibits a computationally useful bistable response. Adviser: Dr. Fadi Alsalee

A Turing-Like Handshake Test for Motor Intelligence

Abstract. In the Turing test, a computer model is deemed to “think intelligently ” if it can generate answers that are not distinguishable from those of a human. This test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, with the human hand movement being a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human, artificial, or a linear combination of the two). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a forced-choice method and ask which of two systems is more humanlike. By comparing a given model with a weighted sum of human and artificial systems, we fit a psychometric curve to the answers of the interrogator and extract a quantitative measure for the computer model in terms of similarity to the human handshake

Complementary Situational Awareness for an Intelligent Telerobotic Surgical Assistant System

Robotic surgical systems have contributed greatly to the advancement of Minimally Invasive Surgeries (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. In this work, these limitations are addressed by developing a computational framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. However, developing such a system to provide real-time situational awareness requires that many technical challenges be met. To estimate intraoperative organ information continuous palpation primitives are required. Intraoperative surface information needs to be estimated in real-time while the organ is being palpated/scanned. The model of the task environment needs to be updated in near real-time using the estimated organ geometry so that the force-feedback applied on the surgeon's hand would correspond to the actual location of the model. This work presents a real-time framework that meets these requirements/challenges to provide situational awareness of the environment in the task space. Further, visual feedback is also provided for the surgeon/developer to view the near video frame rate updates of the task model. All these functions are executed in parallel and need to have a synchronized data exchange. The system is very portable and can be incorporated to any existing telerobotic platforms with minimal overhead

Multilayer haptic feedback for pen-based tablet interaction

We present a novel, multilayer interaction approach that enables state transitions between spatially above-screen and 2D on-screen feedback layers. This approach supports the exploration of haptic features that are hard to simulate using rigid 2D screens. We accomplish this by adding a haptic layer above the screen that can be actuated and interacted with (pressed on) while the user interacts with on-screen content using pen input. The haptic layer provides variable firmness and contour feedback, while its membrane functionality affords additional tactile cues like texture feedback. Through two user studies, we look at how users can use the layer in haptic exploration tasks, showing that users can discriminate well between different firmness levels, and can perceive object contour characteristics. Demonstrated also through an art application, the results show the potential of multilayer feedback to extend on-screen feedback with additional widget, tool and surface properties, and for user guidance

Spatially-localized correlation of MRI and mechanical stiffness to assess cartilage integrity in the human tibial plateau

Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2002.Includes bibliographical references (p. 216-225).Osteoarthritis is a painful degenerative joint disease affecting millions of people in the U.S. The pathogenesis of articular cartilage disease is characterized by softening of cartilage and loss and disruption of constituent macromolecules including proteoglycans and collagen. In current orthopaedic surgical practice, the gold standard for evaluating articular cartilage integrity is the use of a hand probe during arthroscopy. Mechanical probing, however, is invasive and requires anesthesia. Tightly confined areas of the articular surface can be difficult to reach and assess, and manual probing provides a subjective rather than a quantitative assessment of cartilage mechanical integrity. This thesis was motivated by the desire for a noninvasive and nondestructive means to map the variation in mechanical stiffness of an articular surface. Such a method could potentially have application to guiding surgeons during procedures and quantitatively assessing the efficacy of medical and surgical therapies. It could also potentially provide patient-specific, in vivo tissue mechanical property data for surgical simulation and preoperative procedure planning. The macromolecule glycosaminoglycan (GAG) is a significant determinant of cartilage stiffness. GAG content can be assessed noninvasively in vivo and in vitro by an MRI-based technique known as delayed gadolinium-enhanced magnetic resonance imaging of cartilage (dGEMRIC), which measures the MRI parameter TI after equilibration with the ionic contrast agent Gd(DTPA)2-. With dGEMRIC, TlGd serves as an index of GAG content: we therefore examined whether cartilage stiffness could be related to dGEMRIC-measured TlGd in samples of human tibial plateaus.(cont.) We developed an experimental methodology to permit indentation test sites and regions in dGEMRIC scans to be registered with submillimeter accuracy. We found that the load response to focal indentation (a measure of local stiffness) and locally-averaged TlGd were in general highly correlated (Pearson correlation coefficients r = .80, .90, .64, .81 (p < .002) for four different patient samples, 130 total test locations). We further demonstrated that the observed correlation is not a simple consequence of cartilage thickness effects. We observed that the parameters of the stiffness-TIGd relationship differed in some samples between the region of the tibial plateau covered by the meniscus in vivo and the more central region normally in contact with the femoral condyle. This suggests that another factor such as surface architecture or collagen integrity also influences the indentation response of the articular surface.by Joseph Thomas Samosky.Ph.D

Neglect-Like Effects on Drawing Symmetry Induced by Adaptation to a Laterally Asymmetric Visuomotor Delay

In daily interactions, our sensorimotor system accounts for spatial and temporal discrepancies between the senses. Functional lateralization between hemispheres causes differences in attention and in the control of action across the left and right workspaces. In addition, differences in transmission delays between modalities affect movement control and internal representations. Studies on motor impairments such as hemispatial neglect syndrome suggested a link between lateral spatial biases and temporal processing. To understand this link, we computationally modeled and experimentally validated the effect of laterally asymmetric delay in visual feedback on motor learning and its transfer to the control of drawing movements without visual feedback. In the behavioral experiments, we asked healthy participants to perform lateral reaching movements while adapting to delayed visual feedback in either left, right, or both workspaces. We found that the adaptation transferred to blind drawing and caused movement elongation, which is consistent with a state representation of the delay. However, the pattern of the spatial effect varied between conditions: whereas adaptation to delay in only the left workspace or in the whole workspace caused selective leftward elongation, adaptation to delay in only the right workspace caused drawing elongation in both directions. We simulated arm movements according to different models of perceptual and motor spatial asymmetry in the representation of delay and found that the best model that accounts for our results combines both perceptual and motor asymmetry between the hemispheres. These results provide direct evidence for an asymmetrical processing of delayed visual feedback that is associated with both perceptual and motor biases that are similar to those observed in hemispatial neglect syndrome

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world