Series
IRIM Seminar Series

Series Type
Event Series
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Associated Organization(s)
Associated Organization(s)

Publication Search Results

Now showing 1 - 10 of 73
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    Computational Surgery: Helping Surgeons Avoid Mistakes with Better Robots
    (Georgia Institute of Technology, 2017-11-08) Kowalewski, Timothy M.
    Preventable medical errors are the third leading cause of death in the United States. Despite over a decade of clinician-led efforts in policy and education, this issue remains. In the meantime, hospitals have adopted surgical robots at a dramatic pace. This provides opportunities to augment the art of surgery with more rigorous, quantitative science. This gives rise to the field of computational surgery which promises to address long-standing challenges in healthcare like the prevalence of human error. This talk will focus on two research problems in this area. First, how do we quantify and improve the existing skills of a surgeon? This requires a method whose scores correlate with patient outcomes, that can scale to cope with 51 million annual surgeries in the United States, and that can generalize across the diversity surgical procedures or specialties. Second, how can we build new robotic tools that render surgical tasks fundamentally easier, perhaps making errors impossible in the first place? This will survey multiple topics such as policy-blended human-robot shared control to ensure safety in robotic tissue grasping; novel patient-specific catheter robots that safely remove plaque via inverse design of soft robots and a theranostic excimer laser; and robotic 3D bioprinting directly onto moving human anatomy to explore new reconstructive procedures.
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    Vision Based Navigation and Tracking with Small UAVs
    (Georgia Institute of Technology, 2017-11-01) Beard, Randal W.
    This talk will describe our current work on vision-based autonomous navigation and tracking using small UAVs and provide an overview of two ongoing projects. The first project is relative navigation in GPS degraded environments. There are many applications where GPS is either restricted or denied. We have developed an architecture that uses a relative front end to navigate relative to key frames, and then opportunistically uses GPS measurements and SLAM-style loop closures in a back-end process to provide global context. We will show some recent flight results that demonstrate robustness to GPS failure and degradation. The second project we will discuss is robust tracking of multiple ground-based targets from an airborne platform. We will present a new multiple target tracking algorithm that is based on the random sample consensus (RANSAC) algorithm widely used in computer vision. A recursive version of the RANSAC algorithm will be discussed, and its extension to tracking multiple dynamic objects will be explained. The performance of R-RANSAC will be compared to state of the art target tracking algorithms in the context of problems that are relevant to UAV applications.
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    Developing Sensing and Robotics Technologies for Plant Phenomics
    (Georgia Institute of Technology, 2017-10-25) Li, Changying
    Feeding a world population of 9 billion people by 2050 amidst increasing climate variability is one of the greatest challenges facing humanity. The genomics revolution provides unprecedented power to develop new and advanced crop cultivars with the gene combinations needed to address these global challenges. However, rapid and repeatable measurement of crop phenotypic parameters remains a major bottleneck in plant genomics and breeding programs. High-throughput phenotyping technologies that can quickly and repeatedly scan tens of thousands of individuals using an array of advanced sensor and data analytics tools are critical to improving the ability of scientists to dissect the genetics of quantitative traits such as yield and stress tolerance. Our interdisciplinary team is developing a robot-assisted field-based high throughput phenotyping system that integrates both ground and unmanned aerial elements to quantitatively measure a suite of key traits iteratively throughout the growing season. This project is expected to unmask plant responses that will inform a new level and quality of decision-making in the selection of crop genotypes for specific production conditions. A deep learning convolutional neural network was used to identify flowers and the flowering peak of cotton plants. The task coordination between ground and aerial vehicles will result in new discoveries in the area of partitioning and coverage control. In a different but related project, the talk will introduce a Berry Impact Recording Device (BIRD) sensor that has been successfully developed to simulate a real berry to quantitatively measure mechanical impacts on the real fruit created by machine harvesters, packing lines, and transportation vehicles.
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    The Evolution of Soft Robotics
    (Georgia Institute of Technology, 2017-10-18) Shepherd, Robert
    The field of soft mechanisms and sensors provides an exciting opportunity for new hardware development in robotics, a field that is becoming more and more important. This talk describes the development of soft mechanisms, sensors, and their integration into robots for purposes that span from biomimicry, biomedical devices, to virtual reality immersion. My research group, the Organic Robotics Laboratory (ORL), chooses to use intrinsically soft elastomers to compose our robots and have created sensors based on optical waveguides, actuators based on poroelastic foams, and color changing robots based on stretchable, light emitting capacitors. The materials, processing, and mechanics of these systems will be discussed, as well as the potential for future development and integration of these (and other) systems.
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    Cyber Human Interaction: A Control Systems/Robotics Perspective on Functional Electrical Stimulation
    (Georgia Institute of Technology, 2017-10-04) Dixon, Warren
    Application of an electric field across skeletal muscle causes muscle contractions that produce limb movement. Clinicians have long prescribed electrical stimulation as a means to strengthen muscle; however, clinicians have had a growing interest in electrical stimulation to evoke coordinated limb motions for functional tasks such as cycling. Motivation for such a cybernetic system includes advanced rehabilitative outcomes (i.e., neuroplasticity and restoration of function) for individuals with neurological disorders. A challenge to developing these outcomes is that muscle activation dynamics are uncertain and nonlinear, and the dynamics of limb motion also require the coordinated switching among multiple muscle groups. Moreover, artificial stimulation of the muscle is highly inefficient, leading to rapid muscle fatigue, which can limit the therapeutic outcomes. This talk focuses on how perspectives from and advances in robotics/automation/control systems can be used to overcome these challenges. Underlying theories and experimental results for various closed-loop electrical stimulation methods will be described, including recent advances in cybernetic cycling where a robotic bicycle is combined with an electrically stimulated person to facilitate various rehabilitative objectives.
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    Autonomous, Agile, Vision‐Controlled Drones: From Frame to Event Vision
    (Georgia Institute of Technology, 2017-09-22) Scaramuzza, Davide
    Autonomous quadrotors will soon play a major role in search‐and‐rescue and remote‐inspection missions, where a fast response is crucial. Quadrotors have the potential to navigate quickly through unstructured environments, enter and exit buildings through narrow gaps, and fly through collapsed buildings. However, their speed and maneuverability are still far from those of birds. Indeed, agile navigation through unknown, indoor environments poses a number of challenges for robotics research in terms of perception, state estimation, planning, and control. In this talk, I will show that active vision is crucial in order to plan trajectories that improve the quality of perception. Also, I will talk about our recent results on event based vision to enable low latency sensory motor control and navigation in low light and high dynamic environment, where traditional vision sensor fail.
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    Stochastic Models in Robotics
    (Georgia Institute of Technology, 2017-04-20) Chirikjian, Gregory
    Many stochastic problems of interest in engineering and science involve random, rigid-body motions. In this talk, a variety of stochastic phenomena that evolve on the group of rigid-body motions will be discussed together with tools from harmonic analysis and Lie theory to solve the associated equations. These phenomena include mobile robot path planning and camera calibration. Current work on multi-robot team diagnosis and repair, information fusion, and self-replicating robots will also be discussed. In order to quantify the robustness of such robots, measures of the degree of environmental uncertainty that they can handle need to be computed. The entropy of the set of all possible arrangements (or configurations) of spare parts in the environment is one example of such a measure and has led us to study problems at the foundations of statistical mechanics and information theory. These and other topics in robotics lend themselves to the same mathematical tools, which also will be discussed in this talk.
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    Snakes and Spiders, Robots and Geometry
    (Georgia Institute of Technology, 2017-04-12) Hatton, Ross L.
    Locomotion and perception are common threads between robotics and biology. Understanding these phenomena at a mechanical level involves nonlinear dynamics and the coordination of many degrees of freedom. In this talk, I will discuss geometric approaches to organizing this information in two problem domains: 1) Undulatory locomotion of snakes and swimmers; and 2) vibration propagation in spider webs. In the first section, I will discuss how differential geometry and Lie Group Theory provide insight into the locomotion of undulating systems through a vocabulary of lengths, areas, and curvatures. In particular, a tool called the Lie Bracket combines these geometric concepts to describe the effects of cyclic changes in the locomotor’s shape, such as the gaits used by swimming or crawling systems. Building on these results, I will demonstrate that the geometric techniques are useful beyond the “clean” ideal systems on which they have traditionally been developed, and can provide insight into the motion of systems with considerably more complex dynamics, such as locomotors in granular media. In the second section, I will turn my attention to vibration propagation through spiders’ webs. Due to poor eyesight, many spiders rely on web vibrations for situational awareness. Web-borne vibrations are used to determine the location of prey, predators, and potential mates. The influence of web geometry and composition on web vibrations is important for understanding spider’s behavior and ecology. Past studies on web vibrations have experimentally measured the frequency response of web geometries by removing threads from existing webs. The full influence of web structure and tension distribution on vibration transmission; however, has not been addressed in prior work. We have constructed physical artificial webs and computer models to better understand the effect of web structure on vibration transmission. These models provide insight into the propagation of vibrations through the webs, the frequency response of the bare web, and the influence of the spider’s mass and stiffness on the vibration transmission patterns.
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    Examining the Slow, Noisy, and Complex Process of Technology Adoption
    (Georgia Institute of Technology, 2017-03-31) Haltiwanger, John C.
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    Shared Control of Functional Electrical Stimulation and an Electric Motor in a Hybrid Neuroprosthesis
    (Georgia Institute of Technology, 2017-03-08) Sharma, Nitin
    Functional Electrical Stimulation (FES) can be used to artificially activate paralyzed lower limb muscles to restore walking and standing function in persons with neurological disorders. Despite its potential, FES-based walking neuroprosthesis has achieved limited acceptability among persons with paraplegia. This low acceptance is primarily due to the early onset of muscle fatigue during FES and difficulty in obtaining a consistent and reliable response from the paralyzed muscle using traditional control methods. We are employing a hybrid strategy that integrates FES with a powered exoskeleton to overcome these hurdles. This hybrid strategy has several advantages. The main advantage is that the effects of muscle fatigue and any inconsistent response from FES can be compensated by the active exoskeleton, which can potentially lead to improved functional mobility in users with neurological impairments. Other advantages include a reduction in the overall weight of the exoskeleton and neuroplastic improvements in the neuromuscular system due to FES. However, closed-loop control methods are required to effectively integrate FES with a powered exoskeleton because the hybrid combination leads to redundancy in actuation and needs criteria to allocate control between FES and an electric motor. I will present algorithms and models recently developed by our research group to control the hybrid exoskeleton. These methods include: 1) a muscle fatigue model to inform the onset of muscle fatigue and muscle recovery during FES, 2) Shared control of FES and electric motor based on the fatigue model, and 3) muscle synergy inspired control of a hybrid walking exoskeleton.