RI Seminar
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 [...]
Light-Sensitive Displays
Abstract: Nobel prize winner M. G. Lippmann described his dream of an ideal display as a “window into the world.” “While the current most perfect photographic print only shows one aspect of reality, reduced to a single image fixed in a plane, the direct view of reality offers, as we know, infinitely more variety.” Changing [...]
What People See in a Robot: A New Look at Human-Like Appearance
Abstract: A long-standing question in HRI is what effects a robot’s human-like appearance has on various psychological responses. A substantial literature has demonstrated such effects on liking, trust, ascribed intelligence, and so on. Much of this work has relied on a construct of uni-dimensional low to high human-likeness. I introduce evidence for an alternative view according to which [...]
Safe Learning in Robotics
Abstract: A great deal of research in recent years has focused on robot learning. In many applications, guarantees that specifications are satisfied throughout the learning process are paramount. For the safety specification, we present a controller synthesis technique based on the computation of reachable sets, using optimal control and game theory. In the first part [...]
Bipolar Robotics – From the Arctic to the Antarctic with a stop for Fisheries in the middle latitudes.
Abstract: The Arctic, Antarctic and Greenland remain some of the least explored parts of the planet. This talk looks at efforts over the last decade to explore areas under-ice which have traditionally been difficult to access. The focus of the talk will be on the robots, the role of communications over low bandwidth acoustic links, [...]
Learning Robot Manipulation Skills through Experience and Generalization
Abstract: In the future, robots could be used to take care of the elderly, perform household chores, and assist in hazardous situations. However, such applications require robots to manipulate objects in unstructured and everyday environments. Hence, in order to perform a wide range of tasks, robots will need to learn manipulation skills that generalize between [...]
Signal to Symbol (via Skills)
Abstract: While recent years have seen dramatic progress in the development of affordable, general-purpose robot hardware, the capabilities of that hardware far exceed our ability to write software to adequately control. The key challenge here is one of abstraction: generally capable behavior requires high-level reasoning and planning, but perception and actuation must ultimately be performed [...]
Multi-Modal Geometric Learning for Grasping
Abstract: In this talk, we will describe methods to enable robots to grasp novel objects using multi-modal data and machine. The starting point is an architecture to enable robotic grasp planning via shape completion using a single occluded depth view of objects. Shape completion is accomplished through the use of a 3D CNN. The network [...]
Building a Force-Controlled Actuator (Company)
Abstract: In 2014, I was lucky enough to be one of 5 people to start HEBI Robotics, with the dream of eventually making the task of building custom robots as easy as building with Lego. A few years later we are now 10 people, and our first product, a series of modular force-controlled actuators, is [...]
Minimalist Visual Perception and Navigation for Consumer Drones
Abstract: Consumer drone developers often face the challenge of achieving safe autonomous navigation under very tight size, weight, power, and cost constraints. In this talk, I will present our recent results towards a minimalist, but complete perception and navigation solution utilizing only a low-cost monocular visual-inertial sensor suite. I will start with an introduction of [...]
Social Perception for Machines
Abstract: Despite decades of progress, machines remain intelligent tools rather than collaborative partners in individual human enterprise. A key reason is that machine perception of inter-personal communication is largely unsolved and a computationally accessible representation of such behavior remains elusive. In this talk, I will describe our research arc over the past decade at CMU [...]
Geometry Processing in The Wild
Abstract: Geometric data abounds, but our algorithms for geometry processing are failing. Whether from medical imagery, free-form architecture, self-driving cars, or 3D-printed parts, geometric data is often messy, riddled with "defects" that cause algorithms to crash or behave unpredictably. The traditional philosophy assumes geometry is given with 100% certainty and that algorithms can use whatever [...]
Self Driving Cars and AI: Transforming our cities and our lives
Abstract: Artificial intelligence and machine learning are critical to reaching full autonomy in self driving cars. I will present two autonomy systems along with the use of machine learning in each of them. I will summarize recent progress in commercializing these systems and make some observations about the potential impact of these systems in our [...]
Robotic Morphing Matter
Abstract: Morphing matter harnesses the programmability in material structures and compositions to achieve transformative behaviors and integrates sensing, actuation, and computation to create adaptive and responsive material systems. These material systems can be leveraged to design soft robots, self-assembling furniture, adaptive fabrics, and self-folding foods. In this talk, Lining presents the recent works in the [...]
The Mechanical Side of Artificial Intelligence
Abstract: Artificial Intelligence typically focuses on perception, learning, and control methods to enable autonomous robots to make and act on decisions in real environments. On the contrary, our research is focused on the design, mechanics, materials, and manufacturing of novel robot platforms that make the perception, control, or action easier or more robust for natural, unstructured, and [...]
Three surprises and a story of prison education
Abstract: I will talk about three results that surprised me. First, I will show that the free configuration space of an elastic wire is path-connected, a result that makes easy a manipulation planning problem that was thought to be hard. Second, I will show a linear relationship between stimulation parameters, skin impedance, and sensation intensity [...]
Robots Learning from Human Teachers
Abstract: In this talk I will cover some of the recent work out of the Socially Intelligent Machines Lab at UT Austin (http://sim.ece.utexas.edu/research.html). The vision of our research is to enable robots to function in dynamic human environments by allowing them to flexibly adapt their skill set via learning interactions with end-users. We explore the ways in which [...]
Creative Robots with Deep Reinforcement Learning
Recent advances in Deep Reinforcement Learning (DRL) algorithms provided us with the possibility of adding intelligence to robots. Recently, we have been applying a variety of DRL algorithms to the tasks that modern control theory may not be able to solve. We observed intriguing creativity from robots when they are constrained in reaching a certain [...]
Active Learning in Robot Motion Control
Abstract: Motion motivated by information needs can be found throughout natural systems, yet there is comparatively little work in robotics on analyzing and synthesizing motion for information. Instead, engineering analysis of robots and animal motion typically depends on defining objectives and rewards in terms of states and errors on states. This is how we formulate [...]