RI Seminar
Machine Learning For Modeling Real-World Dynamical Systems
Event Location: NSH 3305Bio: Byron Boots is an Assistant Professor in the School of Interactive Computing and the College of Computing at Georgia Tech. He directs the Georgia Tech Robot Learning Lab, which is affiliated with the Center for Machine Learning, the Institute for Data Engineering and Science, and the Institute for Robotics and Intelligent [...]
The Next Frontier in AI: Unsupervised Learning
Event Location: McConomy Auditorium, CUCBio: Yann LeCun is Director of AI Research at Facebook, and Silver Professor of Data Science, Computer Science, Neural Science, and Electrical Engineering at New York University, affiliated with the NYU Center for Data Science, the Courant Institute of Mathematical Science, the Center for Neural Science, and the Electrical and Computer [...]
Autonomous Intelligent Service Robots: Learning and Explanations in Human-Robot Interaction
Manuela Veloso Herbert A Simon University Professor, Carnegie Mellon Abstract We research on autonomous mobile robots with a seamless integration of perception, cognition, and action. In this talk, I will first introduce our CoBot service robots and their novel localization and symbiotic autonomy, which enable them to consistently move in our buildings, now for more [...]
Beyond Geometric Path Planning: Paradigms and algorithms for modern robotics
Kris Hauser Associate Professor, Duke University Abstract The development of fast randomized algorithms for geometric path planning – computing collision-free paths for high dimensional systems – was a major achievement in the field of motion planning in the 2000's. But since then, recent advances in affordable robot sensors, actuators, and systems have changed the robotics [...]
Pathway Toward Vision Restoration, Artificial Vision, Artificial Retina, Optogenetics
José Alain Sahel, MD Professor & Chairman, Department of Ophthalmology, University of Pittsburgh, School of Medicine Abstract Progress in ophthalmology over the past decade moved preclinical data to clinical proof-of-concept studies bringing innovative therapeutic strategies to the market. Diseases such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD) destroy photoreceptors but leave intact and [...]
Towards Agile Flight of Vision-controlled Micro Flying Robots: from Active Vision to Event-based Vision
Davide Scaramuzza Assistant Professor of Robotics, University of Zurich Abstract 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 [...]
e-Intangible Heritage
Event Location: NSH 1305Bio: Dr. Katsushi Ikeuchi is a Principal Researcher of Microsoft Research Asia, stationed at Microsoft Redmond campus. He received a Ph.D. degree in Information Engineering from the University of Tokyo in 1978. After working at Artificial Intelligence Lab of Massachusetts Institute of Technology as a pos-doc fellows for three years, Electrotechnical Lab [...]
Katsushi Ikeuchi : e-Intangible Heritage
Katsushi Ikeuchi Principal Researcher, Microsoft Research Asia Abstract Tangible heritage, such as temples and statues, is disappearing day-by-day due to human and natural disaster. In e-tangible heritage, such as folk dances, local songs, and dialects, has the same story due to lack of inheritors and mixing cultures. We have been developing methods to preserve such [...]
From Drones To Robots, The Road To Make Technologies More Accessible
Shuo Yang Director of Intelligent Navigation Technologies, DJI Abstract Over the past decade, DJI has developed several world-leading drone products, turning cutting-edge technologies such as high resolution image transmission, visual odometry, and learning-based object tracking into affordable commercial products. Along with all these technological successes, DJI is exploring innovative ways to make them more accessible. [...]
Stabilizing the Unstable Brain
Noah Cowan Associate Professor of Mechanical Engineering, Johns Hopkins University Abstract The nervous system is arguably the most sophisticated control system in the known universe, riding at the helm of an equally sophisticated plant. Understanding how the nervous system encodes and processes sensory information, and then computes motor action, therefore, involves understanding a closed loop. [...]
Robot Skill Learning: From the Real World to Simulation and Back
Event Location: NSH 1305Bio: Dr. Peter Stone is the David Bruton, Jr. Centennial Professor and Associate Chair of Computer Science, as well as Chair of the Robotics Portfolio Program, at the University of Texas at Austin. In 2013 he was awarded the University of Texas System Regents' Outstanding Teaching Award and in 2014 he was [...]
Robot Skill Learning: From the Real World to Simulation and Back
Peter Stone David Bruton, Jr. Centennial Professor, The University of Texas at Austin Abstract For autonomous robots to operate in the open, dynamically changing world, they will need to be able to learn a robust set of interacting skills. This talk begins by introducing "Overlapping Layered Learning" as a novel hierarchical machine learning paradigm for [...]
Deep Robotic Learning
Sergey Levine Assistant Professor, UC Berkeley Abstract Deep learning methods have provided us with remarkably powerful, flexible, and robust solutions in a wide range of passive perception areas: computer vision, speech recognition, and natural language processing. However, active decision making domains such as robotic control present a number of additional challenges, standard supervised learning methods [...]
Robots for the social good: Identifying and addressing organizational and societal factors in the design and use of robots
Event Location: NSH 1305Bio: I am an Associate Professor of Informatics and Cognitive Science at Indiana University, Bloomington, where I founded and direct the R-House Human-Robot Interaction Lab. My work combines the social studies of computing, focusing particularly on the design, use, and consequences of socially interactive and assistive robots in different social and cultural [...]
Selma Sabanovic: Robots for the social good: Identifying and addressing organizational and societal factors in the design and use of robots
Selma Sabanovic Associate Professor of Informatics and Cognitive Science, Indiana University Bloomington Additional Information Host: Aaron Steinfeld Appointments: Stephanie Matvey Abstract Robots are expected to become ubiquitous in the near future, working alongside and with people in everyday environments to provide various societal benefits. In contrast to this broad ranging social vision for robotics applications, [...]
Robotic Manipulation under clutter and uncertainty with and around people
Abstract Robots manipulate with super-human speed and dexterity on factory floors. But yet they fail even under moderate amounts of clutter or uncertainty. However, human teleoperators perform remarkable acts of manipulation with the same hardware. My research goal is to bridge the gap between what robotic manipulators can do now and what they are capable [...]
Sven Koenig: Progress on Multi-Robot Path Finding
Abstract Teams of robots often have to assign target locations among themselves and then plan collision-free paths to their target locations. Examples include autonomous aircraft towing vehicles and automated warehouse systems. For example, in the near future, autonomous aircraft towing vehicles might tow aircraft all the way from the runways to their gates (and vice [...]
David Held: Robots Learning to Understand Environmental Changes
Abstract Robots today are typically confined to operate in relatively simple, controlled environments. One reason for these limitation is that current methods for robotic perception and control tend to break down when faced with occlusions, viewpoint changes, poor lighting, unmodeled dynamics, and other challenging but common situations that occur when robots are placed in the [...]
Toward Natural Interactions With Assistive Robots
Abstract Robots can help people live better lives by assisting them with the complex tasks involved in everyday activities. This is especially impactful for people with disabilities, who can benefit from robotic assistance to increase their independence. For example, physically assistive robots can collaborate with people in preparing a meal, enabling people with motor impairments [...]
On-Demand Machine Knitting for Everyone
Abstract: Knitting machines are general-purpose fabrication devices that can robustly create intricate 3D surfaces from yarn by cleverly actuating thousands of mechanical needles. Knitting machines are an established feature of the textiles production landscape, in use today to make everything from socks to sweaters. However, the current design tools for machine knitting are sorely lacking [...]
AI, Robotics, and Autonomous Vehicle Development at Ford Motor Company
Notice: The Location for these event has changed! The event will now take place in 6115 Gates Hillman Center. Education: Ph.D. in Physics, University of Michigan M.S. in Physics, Michigan State University B.S. in Physics & Mathematics, University of Wisconsin – River Falls Abstract: This presentation will highlight the history of autonomous vehicle development at [...]
Modeling Human Movements for Robotics
Abstract: Creating realistic virtual humans has traditionally been considered a research problem in Computer Animation primarily for entertainment applications. With the recent breakthrough in collaborative robots and deep reinforcement learning, accurately modeling human movements and behaviors has become a common challenge faced by researchers in robotics, artificial intelligence, as well as Computer Animation. In this [...]
What Matters for Deformable Object Manipulation
Abstract: Deformable objects such as cables and clothes are ubiquitous in factories, hospitals, and homes. While a great deal of work has investigated the manipulation of rigid objects in these settings, manipulation of deformable objects remains under-explored. The problem is indeed challenging, as these objects are not straightforward to model and have infinite-dimensional configuration spaces, [...]
Optimizing ankle prostheses to improve walking in transtibial amputees
Abstract: With a prosthetic device, people with a lower limb amputation can remain physically active, but most do not achieve medically recommended physical activity standards and are therefore at a greater risk of obesity and cardiovascular disease. Their reduced activity may be attributed to the 10 - 30% increase in energetic cost during walking compared [...]
Exploring Human-Robot Trust during Emergencies
Abstract: This talk presents our experimental results related to human-robot trust involving more than 2000 paid subjects exploring topics such as how and why people trust a robot too much and how broken trust in a robot might be repaired. From our perspective, a person trusts a robot when they rely on and accept the [...]
Deep Structured Models for Human Activity Recognition
Abstract: Visual recognition involves reasoning about structured relations at multiple levels of detail. For example, human behaviour analysis requires a comprehensive labeling covering individual low-level actions to pair-wise interactions through to high-level events. Scene understanding can benefit from considering labels and their inter-relations. In this talk I will present recent work by our group building [...]
Level Set Models for Computer Graphics
ABSTRACT A level set model is a deformable implicit model that has a regularly-sampled representation. It is defined as an iso-contour, i.e. a level set, of some implicit function f. The contour is deformed by solving a partial differential equation on a sampling of f, an image in 2D and a volume dataset in 3D. [...]
“Does it look right? – Why capture and reconstruction quality really matter.”
Special RI Seminar Please Note Different Day and Time Abstract: At first sight, 3D reconstruction can be considered a solved problem. The principles are well understood and we can reconstruct a wide range of objects and scenes using active as well as passive reconstruction approached. However, most of these reconstructions are not convincing when really [...]
Factor Graphs and Automatic Differentiation for Flexible Inference in Robotics and Vision
PLEASE NOTE: THIS SEMINAR WILL NOT BE RECORDED Abstract: Simultaneous Localization and Mapping (SLAM) and Structure from Motion (SFM) are important and closely related problems in robotics and vision. I will review how SLAM, SFM and other problems in robotics and vision can be posed in terms of factor graphs, which provide a graphical language [...]
Long Duration Autonomy With Applications to Persistent Environmental Monitoring
Abstract: By now, we have a fairly good understanding of how to design coordinated control strategies for making teams of mobile robots achieve geometric objectives in a distributed manner, such as assembling shapes or covering areas. But, the mapping from high-level tasks to geometric objectives is not well understood. In this talk, we investigate this [...]
Marine Robotics: Planning, Decision Making, and Learning
Abstract: Underwater gliders, propeller-driven submersibles, and other marine robots are increasingly being tasked with gathering information (e.g., in environmental monitoring, offshore inspection, and coastal surveillance scenarios). However, in most of these scenarios, human operators must carefully plan the mission to ensure completion of the task. Strict human oversight not only makes such deployments expensive and [...]
Signal Processing – From Images to Surfaces
Abstract: In this talk we will revisit some classical techniques from image processing and explore what is involved in translating them to the context of surfaces. We will show that by leveraging existing methodology from discrete differential geometry, it is often easy to extend the image-based techniques so that they can be used to edit [...]
Bio-inspired dynamics for multi-agent decision-making
Abstract: I will present distributed decision-making dynamics for multi-agent systems, motivated by studies of animal groups, such as house-hunting honeybees, and their extraordinary ability to make collective decisions that are both robust to disturbance and adaptable to change. The dynamics derive from principles of symmetry, consensus, and bifurcation in networked systems, exploiting instability as a [...]
Robotics-Inspired Implantable Passive Mechanisms to Surgically Re-Engineer the Human Body
Abstract: Tendon-transfer surgeries are performed for a variety of conditions such as stroke, palsies, trauma, and congenital defects. The surgery involves re-routing a tendon from a nonfunctioning muscle to a functioning muscle to partially restore lost function. However, a fundamental aspect of the current surgery, namely the suture that attaches the tendon(s) to the muscles, [...]
Rendering Material Properties through Touch
Abstract: Humans haptically perceive the material properties of objects, such as roughness and compliance, through signals from sensory receptors in skin, muscles, tendons, and joints. Approaches to haptic rendering of material properties operate by stimulating, or attempting to stimulate, some or all of these receptor populations. My talk will describe research on haptic perception of [...]
From Automation to Autonomy and the Ubiquity of Moral Decision Making
Abstract: I argue that there is an important sense in which all decisions are moral decisions and I explore some implications of this insight (and its denial) for the design and human impacts of increasingly complex automated systems and emerging autonomous systems. This insight is obscured when we think about automated systems by the social [...]
Learning to Drive
Abstract: Why is our understanding of sensorimotor control behind our understanding of perception? I will talk about structural differences between perception and control, and how these differences can be mitigated to help advance sensorimotor control systems. Judicious use of simulation can play an important role and I will describe some simulation tools that we have [...]
Imaging the World One Photon at a Time
Abstract: The heart of a camera and one of the pillars for computer vision is the digital photodetector, a device that forms images by collecting billions of photons traveling through the physical world and into the lens of a camera. While the photodetectors used by cellphones or professional DSLR cameras are designed to aggregate as [...]
Carnegie Mellon University
Lesson Learned from Two Decades of Robotics Development and Thoughts on Where We Go from Here
Abstract: In this talk, Herman Herman will offer various lessons learned from developing various robots for the last 2 decades at the National Robotics Engineering Center. He will also offer his perspective on the future of autonomous robots in various industries, including self-driving cars, material handling and consumer robotics. Bio: Dr. Herman Herman is the [...]
Factor Graphs for Robot Perception
Abstract: Factor graphs have become a popular tool for modeling robot perception problems. Not only can they model the bipartite relationship between sensor measurements and variables of interest for inference, but they have also been instrumental in devising novel inference algorithms that exploit the spatial and temporal structure inherent in these problems. I will overview [...]