Geometry is concerned with the properties of configurations of points, lines, and circles, while topology is concerned with space, dimension, and transformation. Geometry is also materials independent and scale invariant. By introducing holes and cuts in 2D sheets, we demonstrate dramatic shape change and super-conformability via expanding or collapsing of the hole arrays without deforming individual lattice units. When choosing the cuts and geometry correctly, we show folding into the third dimension, known as kirigami. The kirigami structures can be rendered pluripotent, that is changing into different 3D structures from the same 2D sheet. We explore their potential applications in energy efficient building facade, super-stretchable and shape conformable energy storage devices and medical devices, as well as bioinspired robotics. Programmable shape-shifting materials can take different physical forms to achieve multifunctionality in a dynamic and controllable manner. Through designs of geometric surface patterns, e.g. microchannels, we program the orientational elasticity in liquid crystal elastomers (LCEs), to direct folding of the 2D sheets into 3D shapes, which can be triggered by heat, light, and electric field. Taking this knowledge of guided inhomogeneous local deformations in LCEs, we then tackle the inverse problem – pre-programming geometry on a flat sheet to take an arbitrary desired 3D shape. Lastly, I will show the prospective of taking geometry to create smart fabrics and tendon-like filaments for soft robotic applications.
Reducing the size and emissions of gas turbine engines used in the aeronautics industry forces manufacturers to explore new operating conditions. An undesirable phenomenon called thermo-acoustic instabilities may occur, caused by the coupling between combustion dynamics and the acoustics of the combustion chamber. To help predict, detect and suppress it, we explore various approaches. We will discuss the design of observers for infinite-dimensional systems, Fourier-based reduced-order modeling as well as a Machine-Learning approach based on high-fidelity simulation data.
Visual perception involves a complex interaction between feedforward and feedback processes. A mechanistic understanding of these processing, and its limitations, is a necessary first step towards elucidating key aspects of perceptual functions and dysfunctions. In this talk, I will review our ongoing effort towards the understanding of how feedback visual processing operates at the level of the thalamus, a dynamic relay station halfway between the retina and the cortex. I will present experimental evidence from several recent electrophysiology studies performed on subjects engaged in visual detection tasks. The results show that modulatory driving provided by top-down processes (the feedback from primary visual cortex) critically influences the ongoing thalamic activity and shapes the message to be delivered to the cortex. When neuromodulatory techniques (Transcranial Magnetic Stimulation or static magnetic fields) are used to transiently disrupt cortical activity two very interesting effects show up: (1) alterations in stimulus detection and (2) the spatial properties of thalamic receptive fields are dramatically modified. Finally, I will show how sensory information can be a powerful tool to interact with the motor system and re-organize altered patterns of movement in neurological disorders such as Parkinson's disease.
Organizers: Daniel Cudeiro
Investigations and control of biological and synthetic nanoscopic species in liquids at the ultimate resolution of single entity, are important in diverse fields such as biology, medicine, physics, chemistry and emerging field of nanorobotics. Progress made to date on trapping and/or manipulating nanoscopic objects includes methods that use permanently imposed force fields of various kinds, such as optical, electrical and magnetic forces, to counteract their inherent Brownian motion.
Why cannot the current robots act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. Progress requires advances in the sensing hardware, but also advances in the software that can exploit the tactile signals. We developed a high-resolution tactile sensor, GelSight, which measures the geometry and traction field of the contact surface. For interpreting the high-resolution tactile signal, we utilize both traditional statistical models and deep neural networks. I will describe my research on both exploration and manipulation. For exploration, I use active touch to estimate the physical properties of the objects. The work has included learning the hardness of artificial objects, as well as estimating the general properties of natural objects via autonomous tactile exploration. For manipulation, I study the robot’s ability to detect slip or incipient slip with tactile sensing during grasping. The research helps robots to better understand and flexibly interact with the physical world.
Organizers: Katherine J. Kuchenbecker
Abstract: Sequential Monte Carlo (SMC) methods (including the particle filters and smoothers) allows us to compute probabilistic representations of the unknown objects in models used to represent for example nonlinear dynamical systems. This talk has three connected parts: 1. A (hopefully pedagogical) introduction to probabilistic modelling of dynamical systems and an explanation of the SMC method. 2. In learning unknown parameters appearing in nonlinear state-space models using maximum likelihood it is natural to make use of SMC to compute unbiased estimates of the intractable likelihood. The challenge is that the resulting optimization problem is stochastic, which recently inspired us to construct a new solution to this problem. 3. A challenge with the above (and in fact with most use of SMC) is that it all quickly becomes very technical. This is indeed the key challenging in spreading the use of SMC methods to a wider group of users. At the same time there are many researchers who would benefit a lot from having access to these methods in their daily work and for those of us already working with them it is essential to reduce the amount of time spent on new problems. We believe that the solution to this can be provided by probabilistic programming. We are currently developing a new probabilistic programming language that we call Birch. A pre-release is available from birch-lang.org/ It allow users to use SMC methods without having to implement the algorithms on their own.
Organizers: Philipp Hennig
Today’s advances in tactile sensing and wearable, IOT and context-aware computing are spurring new ideas about how to configure touch-centered interactions in terms of roles and utility, which in turn expose new technical and social design questions. But while haptic actuation, sensing and control are improving, incorporating them into a real-world design process is challenging and poses a major obstacle to adoption into everyday technology. Some classes of haptic devices, e.g., grounded force feedback, remain expensive and limited in range. I’ll describe some recent highlights of an ongoing effort to understand how to support haptic designers and end-users. These include a wealth of online experimental design tools, and DIY open sourced hardware and accessible means of creating, for example, expressive physical robot motions and evolve physically sensed expressive tactile languages. Elsewhere, we are establishing the value of haptic force feedback in embodied learning environments, to help kids understand physics and math concepts. This has inspired the invention of a low-cost, handheld and large motion force feedback device that can be used in online environments or collaborative scenarios, and could be suitable for K-12 school contexts; this is ongoing research with innovative education and technological elements. All our work is available online, where possible as web tools, and we plan to push our research into a broader openhaptics effort.
Organizers: Katherine J. Kuchenbecker
Disney Research has been actively pushing the state-of-the-art in digitizing humans over the past decade, impacting both academia and industry. In this talk I will give an overview of a selected few projects in this area, from research into production. I will be talking about photogrammetric shape acquisition and dense performance capture for faces, eye and teeth scanning and parameterization, as well as physically based capture and modelling for hair and volumetric tissues.
Organizers: Timo Bolkart
In this talk I will describe the main types of research questions and neuroimaging tools used in my work in human cognitive neuroscience (with foci in audition and sleep), some of the existing approaches used to analyze our data, and their limitations. I will then discuss the main practical obstacles to applying machine learning methods in our field. Several of my ongoing and planned projects include research questions that could be addressed and perhaps considerably extended using machine learning approaches; I will describe some specific datasets and problems, with the goal of exploring ideas and potentially opportunities for collaboration.
Organizers: Mara Cascianelli
Mechanical removal of blood clots is a promising approach towards the treatment of vascular diseases caused by the pathological clot formation in the circulatory system. These clots can form and travel to deep seated regions in the circulatory system, and result in significant problems as blood flow past the clot is obstructed. A microscopi-cally small helical microrobot offers great promise in the minimally-invasive removal of these clots. These helical microrobots are powered and controlled remotely using externally-applied magnetic fields for motion in two- and three-dimensional spaces. This talk will describe the removal of blood clots in vitro using a helical robot under ultrasound guidance. The talk will briefly introduce the interactions between the helical microrobot and the fibrin network of the blood clots during its removal. It will also introduce the challenges unique to medical imaging at micro-scale, followed by the concepts and theory of the closed-loop motion control using ultrasound feedback. It will then cover the latest experimental results for helical and flagellated microrobots and their biomedical and nanotechnology applications.
Organizers: Metin Sitti
Daniel Renjewski presents research in bipedal gait mechanisms: 'Passive mechanisms for increased power and efficiency in bipedal gait’
Incredible biological capabilities have emerged through evolution. Of special note is the material intelligence that defines the bodies of living things, blurring the line between brain and body. Material robotics research takes the approach of imbuing power, control, sensing, and actuation into all aspects of a (primarily soft) robot body. In this talk, the research topics of material robotics currently underway in the mLab at Oregon State University will be presented. Soft active materials designed and researched in the mLab include liquid metal, biodegradable elastomers, and electroactive fluids. Bioinspired mechanisms include octopus-inspired soft muscles, gecko-inspired adhesives, and snake-like locomotors. Such capabilities, however, introduce new fundamental challenge in making materially-enabled robots. To address these limitation, the mLab is also innovating in techniques to rapidly and scalably manufacture soft materials. Though significant challenges remain to be solved, the development of such soft and materially-enabled components promises to bring robots more and more into our daily lives.
Organizers: Metin Sitti