Generative Point Cloud Modeling with Gaussian Mixture Models for Multi-Robot Exploration
Autonomous exploration in rich 3D environments requires the construction and maintenance of a representation derived from accumulated 3D observations. Volumetric models, which are commonly employed to enable joint reasoning about occupied and free space, scale poorly with the size of the environment. Techniques employed to mitigate this scaling include hierarchical discretization, learning local data summarizations [...]
Carnegie Mellon University
Integrating Model-based Planning with Skill learning for Mobile Manipulation
With an ever-growing demand to automate different day-to-day activities, the task of autonomous manipulation using articulated robots has gained serious traction lately. In this regard, motion planning for manipulation is one of the highly researched topics. The Motion planning for manipulation is often cast as either a model-based planning problem or a machine learning problem. However, both of these [...]
Learning Multi-Modal Navigation for Unmanned Ground Vehicles
Abstract: A robot that operates efficiently in a team with a human in an unstructured outdoor environment must be able to translate commands from a modality that is intuitive to its operator into actions. This capability is especially important as robots become ubiquitous and interact with untrained users. For this to happen, the robot must [...]
Carnegie Mellon University
In-Field Robotic Leaf Grasping and Automated Crop Spectroscopy
Agricultural robotics is a growing field of intelligent automation that is proving to drastically increase the speed and reliability of in-field tasks such as precision seed planting, harvesting, field mapping, and crop monitoring. More specifically, plant breeders are beginning to use robotic systems to record the physical traits of crops throughout the growing season at [...]
Carnegie Mellon University
Soft-matter Artificial Muscle by Electrochemical Surface Oxidation of Liquid Metal
Natural muscles, a result of more than 500 millions years of evolution, are elegant machines that generate force and motion electrochemically. The brief history of robotics does not have the luxury of millions of years to reverse-engineer many aspects of life. The development of artificial muscles therefore seeks to build more muscle-like actuators for robots. [...]
Radiation Source Localization using a Gamma-ray Camera
Radiation source localization is a common and critical task across applications such as nuclear facility decommissioning, radioactive disaster response, and security. Traditional count-based sensors (e.g. Geiger counters) infer range to the source based on the observed number of gamma photons, expected source strength, and assumed intermediate attenuation from the environment. In cluttered 3D settings, such [...]
Carnegie Mellon University
Improving Imitation Learning through Efficient Expert Querying
Learning from demonstration is an intuitive approach to encoding complex behaviors in autonomous agents. Learners have shown success in challenging tasks like autonomous driving, aerial obstacle avoidance, and information gathering, through observation and mimicry alone. State of the art algorithms like Dataset Aggregation (DAgger) have made significant advances over traditional behavior cloning, demonstrating strong theoretical [...]
Carnegie Mellon University
Provably Optimal Design of a Brain-Computer Interface
Abstract: Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. Over the past two decades, much attention has been devoted to the decoding problem: how should recorded [...]
RI Summer Scholars Poster Session Today at 3:30pm in the NSH Perlis Atrium
Come celebrate the contributions of the cohort members, mentors, program partners, and volunteers that make the program possible. Refreshments will be served.
Failure Is an Option: How the Severity of Robot Errors Affects Human-Robot Interactions
Abstract: Just as humans are imperfect, even the best of robots will eventually fail at performing a task. The likelihood of failure increases as robots expand their roles in our lives. Although task failure is a common problem in robotics and human-robot interaction (HRI), there has been little research investigating human tolerance to said failures, [...]
Carnegie Mellon University
Extensions of the Principal Fiber Bundle Model for Locomoting Robots
Abstract: Our goal is to establish a rigorous formulation for modeling the locomotion of a broad class of robotic systems. Recent research has identifi ed a number of systems with the structure of a principal fiber bundle. This framework has led to a number of tools for analysis and motion planning applicable to various robotic [...]
2018 Robotics Institute Picnic
Attention: This events time was changed. The original time was 3pm to 7pm, the event is now occurring from 2pm to 6pm. If you had exported the event to add it to your calendar, please be sure to update the time in your calendar appropriately. Private Event: By Invitation Only SOCIALIZE, EAT, DRINK & [...]
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 [...]
ANA Avatar XPRIZE BRIDGING DISTANCE, TIME, AND CULTURE FOR ALL
"Calling all Carnegie Mellon inventors, creators, and scientists. Are you studying robotics, computer science, psychology, sociology, virtual immersion, sensor technologies, haptics, artificial intelligence or thinking about inventing the future? Have you ever wondered what it would be like to transport your consciousness to another part of the world, and be able to feel the place [...]
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 [...]
Carnegie Mellon University
Scaling up Self-Supervision for Robot Learning
Abstract: A general purpose robot will need to interact with objects in cluttered environments with minimal supervision. Machine learning provides methods that can deal with these complex tasks without explicitly modelling the environment. More recently, deep learning techniques combined with large scale data has revolutionized the fields of computer vision, language processing and reinforcement learning. [...]
Towards better methods of video generation
Abstract: Learning to generate future frames of a video sequence is a challenging research problem with great relevance to reinforcement learning, planning and robotics. Existing approaches either fail to capture the full distribution of outcomes, or yield blurry generations, or both. In this talk I will address two important aspects of video generations: (i) what [...]
Carnegie Mellon University
Safe Data Gathering in Physical Spaces
Abstract: Reliable and efficient acquisition of data from physical spaces has widespread applications in industry, policy, defense, and humanitarian work. Unmanned Aerial Vehicles (UAVs) are an excellent choice for data gathering applications, due to their capability of gaining information at multiple scales. A robust data gathering system needs to reason about multi-resolution nature of information [...]
Robotics Institute Faculty Social
All Robotics Institute faculty are invited to attend these informal team-building business/social events. Beverages and snacks will be provided.
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 [...]
Acquiring and Transferring Generalizable Vision-based Robot Skills
Abstract: In recent years, there have been great advances in policy learning for goal-oriented agents. However, there are still major challenges brought by real-world constraints for teaching highly generalizable and versatile robot policies in a cost efficient and safe manner. In this talk, I will argue that instead of aiming to teach large motion repertoires [...]
Carnegie Mellon University
Robot Learning in Homes – Improving Generalization and Reducing Dataset Bias
Abstract: Data-driven approaches to solving robotic tasks have gained a lot of traction in recent years. However, most existing policies are trained on large-scale datasets collected in curated lab settings. If we aim to deploy these models in unstructured visual environments like people’s homes, they will be unable to cope with the mismatch in data [...]
Learning to localize and anonymize objects with indirect supervision
Abstract: Computer vision has made great strides for problems that can be learned with direct supervision, in which the goal can be precisely defined (e.g., drawing a box that tightly-fits an object). However, direct supervision is often not only costly, but also challenging to obtain when the goal is more ambiguous. In this talk, I [...]
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 [...]
Carnegie Mellon University
Online, Interactive User Guidance for High-dimensional, Constrained Motion Planning
Abstract: We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance [...]
RI Faculty Social
All Robotics Institute faculty are invited to attend this informal team-building business/social event. Beverages and snacks will be provided.
Carnegie Mellon University
MRFMaps: A Representation for Multi-Hypothesis Dense Volumetric SLAM
Abstract: Robust robotic flight requires tightly coupled perception and control. Conventional approaches employ a SLAM algorithm to infer the most likely trajectory and then generate an occupancy grid map using dense sensor data for planning purposes. In such approaches all the robustness and accuracy costs are offset to the SLAM algorithm; if there are any [...]
Carnegie Mellon University
Learning to learn from simulation: Using simulations to learn faster on robots
Abstract: Learning for control is capable of acquiring controllers in novel task scenarios, paving the path to autonomous robots. However, typical learning approaches can be prohibitively expensive in terms of robot experiments, and policies learned in simulation do not transfer directly due to modelling inaccuracies. This encourages learning information from simulation that has a higher [...]
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, [...]
Video Compression for Recognition & Video Recognition for Compression
Abstract: Training robust deep video representations has proven to be much more challenging than learning deep image representations. One reason is: videos are huge and highly redundant. The 'true' and interesting signal often drowns in too much irrelevant data. In the first part of the talk, I will show how to train a deep network [...]
Multimodal Computational Behavior Understanding
Emotions influence our lives. Observational methods of measuring affective behavior have yielded critical insights, but a persistent barrier to their wide application is that they are labor-intensive to learn and to use. An automated system that can quantify and synthesize human affective behavior in real-world environments would be a transformational tool for research and for [...]
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 [...]
Fully Autonomous Drones for Wind Power Turbine Inspection
Abstract: The wind energy industry is growing rapidly. In the U.S. alone, the wind industry invested more than $11 billion in new plants in 2017 and added more than 7,000 megawatts of new capacity, representing 25% of all electric capacity added. One of the biggest challenges to growth remains the high costs of constructing wind [...]
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 [...]
Carnegie Mellon University
Sparse and Dense Methods for Underwater Localization and Mapping with Imaging Sonar
Abstract: Imaging sonars have been used for a variety of tasks geared towards increasing autonomy of underwater vehicles: image registration and mosaicing, vehicle localization, object recognition, mapping, and path planning, to name a few. However, the complexity of the image formation has led many algorithms to make the restrictive assumption that the scene geometry is [...]
Carnegie Mellon University
Deep Interpretable Non-rigid Structure from Motion
Abstract: Current non-rigid structure from motion (NRSfM) algorithms are limited with respect to: (i) the number of images, and (ii) the type of shape variability they can handle. This has hampered the practical utility of NRSfM for many applications within vision. Deep Neural Networks (DNNs) are an obvious candidate to help with such issue. However, [...]
RI Faculty Social All Robotics Institute faculty are invited to attend this informal team-building business/social event
All Robotics Institute faculty are invited to attend this informal team-building business/social event. Our November Robotics Institute Faculty Social will be hosted by Martial Hebert in NSH 4305, from 3:00 to 4:00pm.
Carnegie Mellon University
Autonomous drone cinematographer: Using artistic principles to create smooth, safe, occlusion-free trajectories for aerial filming
Abstract: Autonomous aerial cinematography has the potential to enable automatic capture of aesthetically pleasing videos without requiring human intervention, empowering individuals with the capability of high-end film studios. Current approaches either only handle off-line trajectory generation, or offer strategies that reason over short time horizons and simplistic representations for obstacles, which result in jerky movement and [...]
Carnegie Mellon University
Robot Task Execution by Policy Adaptation and Switching Among Multiple Tasks
Abstract: While mobile robots reliably perform service tasks by accurately localizing and safely navigating while avoiding obstacles, they do not respond in any other way to their surroundings. In this work, we introduce two methods that enable the robots to be more responsive to their environment, including humans and other robots. The first algorithm enables [...]
Visual SLAM with Semantic Scene understanding
Abstract: Simultaneous localization and mapping (SLAM) has been widely used in autonomous robots and virtual reality. It estimates the sensor motion and maps the environment at the same time. The classic sparse feature point map of visual SLAM is limited for many advanced tasks including robot navigation and interactions, which usually require a high-level understanding of [...]
Carnegie Mellon University
Vision with Small Baselines
Abstract: Portable camera sensor systems are becoming more and more popular in computer vision applications such as autonomous driving, virtual reality, robotics manipulation and surveillance, due to the decreasing expense and size of RGB camera. Despite the compactness and portability of the small baseline vision systems, it is well-known that the uncertainty in range finding [...]
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 [...]
Carnegie Mellon University
Machine Imagination: Data-driven User Controllable Visual Content Creation
Abstract: Humans have the remarkable ability to create visual worlds far beyond what could be seen by human eye, including inferring the state of unobserved, imagining the unknown, and thinking about diverse possibilities about what lies in the future. Machines lack this inquisitive ability despite the current revolution in machine learning and computer vision. We [...]
Robotics Institute Administrative Staff Winter Tree Lunch
Please join us for our annual Robotics Institute Administrative Staff Winter Tree Decorating Lunch. A light lunch will be provided but staff-created treats will always be welcomed.
Carnegie Mellon University
Persistent Multi-Robot Mapping in an Uncertain Environment
Abstract: We present a system that addresses the challenge of concurrently mapping, scheduling, and deploying a team of energy-constrained robots to persistently cover an unknown and potentially dynamic environment. This system can passively maintain an accurate representation of occupied space, allowing robots reliable access for monitoring, study, or search and rescue. Current state-of-the-art algorithms only [...]
Robotics Institute Winter Party
Please join us for some fun, food, beverages and conversation! All RI faculty, staff, students and visitors are invited to the Robotics Institute Winter Party! We apologize but due to space limitations in the Atrium we regretfully cannot include family or other non-RI guests.
Carnegie Mellon University
Learning with Clusters
Abstract: Clustering, the problem of grouping similar data, has been extensively studied since at least the 1950's. As machine learning becomes more prominent, clustering has evolved from primarily a data analysis tool into an integrated component of complex robotic and machine learning systems, including those involving dimensionality reduction, anomaly detection, network analysis, image segmentation and [...]
Carnegie Mellon University
Spatiotemporal Understanding of People Using Scenes, Objects, and Poses
Abstract: Humans are arguably one of the most important entities that AI systems would need to understand to be useful and ubiquitous. From autonomous cars observing pedestrians to assistive robots helping the elderly, a large part of this understanding is focused on recognizing human actions, and potentially, their intentions. Humans themselves are quite good at [...]
Faster, Safer, Smaller: The future of autonomy needs all three
Abstract In this talk I will start with state estimation as my PhD work. Very often, state estimation plays a crucial role in a robotic system serving as a building block for autonomy. Challenges are to carry out state estimation in 6-DOF, in real-time at high frequencies, with high precision, robust to aggressive motion and [...]
Carnegie Mellon University
Sensing, Measuring, and Modeling Social Signals in Nonverbal Communication
Abstract: Humans convey their thoughts, emotions, and intentions through a concert of social displays: voice, facial expressions, hand gestures, and body posture, collectively referred to as social signals. Despite advances in machine perception, machines are unable to discern the subtle and momentary nuances that carry so much of the information and context of human communication. [...]
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 [...]
2019 RI Faculty Dinner
RI Faculty Social
All Robotics Institute faculty are invited to attend this informal team-building business/social event. Beverages and snacks will be provided.
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 [...]