Carnegie Mellon University
Underwater Localization and Mapping with Imaging Sonar
Abstract: Acoustic imaging sonars have been used for a variety of tasks intended to increase the autonomous capabilities of underwater vehicles. Among the most critical tasks of any autonomous vehicle are localization and mapping, which are the focus of this work. The difficulties presented by the imaging sonar sensor have led many previous attempts at [...]
Deep Learning for Robotics
Abstract: Programming robots remains notoriously difficult. Equipping robots with the ability to learn would by-pass the need for what otherwise often ends up being time-consuming task specific programming. This talk will describe recent progress in deep reinforcement learning (robots learning through their own trial and error), in apprenticeship learning (robots learning from observing people), and [...]
Temporal Modeling and Data Synthesis for Visual Understanding
Abstract: In this talk, I will present two recent pieces of work on leveraging temporal information and synthetic data to enhance video and image understanding. In the first part, I will introduce a progressive learning framework, Spatio-TEmporalProgressive (STEP), for action detection in videos. STEP is able to more effectively make use of longer temporal information, [...]
Multiple Drone Vision and Cinematography
Abstract: The aim of drone cinematography is to develop innovative intelligent single- and multiple-drone platforms for media production to cover outdoor events (e.g., sports) that are typically distributed over large expanses, ranging, for example, from a stadium to an entire city. The drone or drone team, to be managed by the production director and his/her [...]
Modeling, Design, and Analysis for Intelligent Vehicles: Intersection Management, Security-Aware Design, and Automotive Design Automation
Abstract: Advanced Driver Assistance Systems (ADAS), autonomous functions, and connected applications bring a revolution to automotive systems and software. In this talk, several research topics in the domain of automotive systems and software will be introduced: (1) graph-based modeling, scheduling, and verification for intersection management, (2) security-aware design and analysis considering timing, game theory, and [...]
Carnegie Mellon University
Open-world Object Detection and Tracking
Abstract: Computer vision today excels at recognition in narrow slices of the real world. Our systems seem to accurately detect cats, cars, or chairs, but largely ignore the vast diversity of objects in the world that are absent from our training datasets. Perception in the open world, however, requires detecting and tracking any object, regardless [...]
Carnegie Mellon University
Personalized and weakly supervised learning for Parkinson’s disease symptom detection
Abstract: Parkinson's Disease (PD) is a neurodegenerative disorder that affects approximately one million Americans. Medications exist to manage the symptoms, but doctors must periodically adjust dosage level and frequency as a patient's disease progresses. These adjustments are typically based on observations made during short clinic visits, which provide an incomplete picture of a patient's daily [...]
VR facial animation via multiview image translation
Abstract: A key promise of Virtual Reality (VR) is the possibility of remote social interaction that is more immersive than any prior telecommunication media. However, existing social VR experiences are mediated by inauthentic digital representations of the user (i.e., stylized avatars). These stylized representations have limited the adoption of social VR applications in precisely those [...]
Neural Volumes: Learning Dynamic Renderable Volumes from Images
Abstract: Modeling and rendering of dynamic scenes is challenging, as natural scenes often contain complex phenomena such as thin structures, evolving topology, translucency, scattering, occlusion, and biological motion. Mesh-based reconstruction and tracking often fail in these cases, and other approaches (e.g., light field video) typically rely on constrained viewing conditions, which limit interactivity. We [...]
RI40: Past, Present, and Future
Please plan to join us on Friday, October 25, 2019 as we celebrate 40 years of people, robots, and innovation! 40 years ago Carnegie Mellon University’s Robotics Institute opened its doors with the dream of ushering in a new age of thinking robots. During the ensuing decades, we have experienced many research successes in intelligent [...]
RI40 Seminar: From Direct-Drive to SuperLimb Bionics
In 1980-81 the first Direct-Drive robot was developed at the CMU Robotics Institute. After almost 40 years, Direct-Drive has a renewed interest in the leg robotics community. Robotic legs powered by direct-drive or low gear-reduction motors can better interact with the ground and absorb impacts. In this seminar I will talk about robot design in [...]
Tartan AUV: A Dive into Carnegie Mellon’s RoboSub Team
Abstract: Founded last year, Tartan AUV is Carnegie Mellon’s undergraduate underwater robotics team which competes annually in the RoboSub competition. RoboSub teams must design, build, and test autonomous underwater vehicles that compete each August to complete tasks related to underwater navigation, object detection and manipulation, and acoustic beacon localization. In this talk we will provide [...]
DNA and gammaPNA in programmable nanomaterials for sensing, robotics and manufacturing
Abstract: When programmable nanomaterials are used in conjunction with rapid microfabrication techniques like two photon polymerization, it becomes possible to rapidly prototype microstructures with nanoscale components. In this research presentation I introduce DNA nanotechnology using a commonly used simple nanotube motif, and I will illustrate how nucleic acid nanotubes can be used in sensing, robotics [...]
Towards Lightweight Real-time Hand Reconstruction in Challenging
Abstract: Humans naturally use their hands to interact and communicate with their surroundings. Reconstructing these complex and dexterous hand interactions enables sign-language recognition and translation, better assistive robots, and more immersive human-computer interaction (e.g. for AR and VR). To make hand reconstruction usable for the aforementioned applications and to a wide set of users, the [...]
Soft Robotics challenges: Design, Fabrication, Control, and Motion Planning
Abstract: More and more robots of the future will be soft. A soft body can absorb impact forces from collisions with obstacles, making robots suitable for unpredictable environments and safe for human-robot interaction. However, widespread application of soft robotics in daily life, business, and consumer products have not yet been achieved, because established robotic technologies, [...]
Hybrid Methods for the Integration of Heterogeneous Multimodal Biomedical Data
Abstract: The prevalence of smartphones and wearable devices for health monitoring and widespread use of electronic health records have led to a surge in heterogeneous multimodal healthcare data, collected at an unprecedented scale. My research focuses on developing machine learning techniques that learn salient representations of multimodal, heterogeneous data for biomedical predictive models. The first [...]
Carnegie Mellon University
Online and Consistent Occupancy Grid Mapping
Abstract: Actively exploring and mapping an unknown environment requires integration of both simultaneous localization and mapping (SLAM) and path planning methods. Path planning relies on a map that contains free and occupied space information and is efficient to query, while the role of SLAM is to keep the map consistent as new measurements are continuously [...]
Carnegie Mellon University
A Planning Framework for Persistent, Multi-UAV Coverage with Global Deconfliction
Abstract: Planning for multi-robot coverage seeks to determine collision-free paths for a fleet of robots, enabling them to collectively observe points of interest in an environment. Persistent coverage is a variant of traditional coverage where coverage-levels in the environment decay over time. Thus, robots have to continuously revisit parts of the environment to maintain a [...]
The Robots are Coming – to your Farm! AKA: Autonomous and Intelligent Robots in Unstructured Field Environments
Abstract: What if a team of collaborative autonomous robots grew your food for you? In this talk, I will discuss some key advances in robotics, machine learning, and autonomy that will one day enable teams of small robots to grow food for you in your backyard in a fundamentally more sustainable way than modern mega-farms! [...]
Carnegie Mellon University
‘Unboxing’ anomaly detection and panoptic segmentation
Abstract: Panoptic segmentation is a recent problem in computer vision that attempts to classify each pixel in an image according to its semantic and instance label (accomplishing both semantic segmentation and instance segmentation respectively). Most existing panoptic and instance segmentation methods run a detection-first pipeline, where a bounding box is placed around an object and [...]
Carnegie Mellon University
Self-Supervised Learning on Mobile Robots Using Acoustics, Vibration, and Visual Models to Build Rich Semantic Terrain Maps
Abstract: Humans and robots would benefit from having rich semantic maps of the terrain in which they operate. Mobile robots equipped with sensors and perception software could build such maps as they navigate through a new environment. This information could then be used by humans or robots for better localization and path planning, as well [...]
Self-Driving Cars & AI: Transforming our Cities and our Lives
Abstract: Recent algorithmic and hardware improvements resulted in several success stories in the field of Artificial Intelligence (AI) which impact our daily lives. However, despite its ubiquity, AI is only just starting to make advances in what may arguably have the largest societal impact thus far, the nascent field of autonomous driving. At Uber ATG, [...]
Carnegie Mellon University
Transfers Between Multiple Service Robots
Abstract: With the deployment of more robots, human-robot interaction will no longer be limited to a one-to-one interaction between a user and a robot. Instead, users will likely have to interact with multiple robots, simultaneously or sequentially, throughout their day to receive services and complete different tasks. In this thesis proposal, I am proposing joint [...]
Carnegie Mellon University
Machine Learning Parallelism Could Be Adaptive, Composable and Automated
Abstract: In recent years, the pace of innovations in the fields of machine learning has accelerated. To cope with the sheer computational complexity of training large ML models on large datasets, researchers in SysML have created algorithms and systems that parallelize ML training and inference over multiple CPUs or GPUs, or even multiple computing nodes [...]
MSR Thesis Talk – Matt Martone
Title: Design and Control of a Large Modular Hexapod Abstract: Legged robotic systems have made great strides in recent years, but unlike wheeled robots, limbed locomotion does not scale well. Long legs demand huge torques, driving up actuator size and onboard battery mass. This relationship results in massive structures that lack the safety, portability, [...]
Improving Robot and Deep Reinforcement Learning via Quality Diversity and Open-Ended Algorithms
Abstract: Quality Diversity (QD) algorithms are those that seek to produce a diverse set of high-performing solutions to problems. I will describe them and a number of their positive attributes. I will then summarize our Nature paper on how they, when combined with Bayesian Optimization, produce a learning algorithm that enables robots, after being damaged, to adapt in 1-2 minutes [...]
Carnegie Mellon University
Online Kinodynamic Planning for Teams of Aerial Robots in 3-D Workspaces
Abstract: An efficient online planning or replanning methodology is a critical requirement for scalable and responsive real world multi-robot deployments. The need to replan typically stems from the invalidation of existing plans due to incomplete knowledge of the environment, or, from scenarios that necessitate changing goal locations in response to evolving application requirements. In this [...]
Go, fastMRI, and Minecraft: Exploring the limits of AI
Abstract: The application of AI across various domains demonstrates both the promise of existing techniques but also their limitations. In this talk, I explore three recent projects and how they shed light on the progress of AI and the challenges to come. These projects include ELF OpenGo a reimplementation of AlphaZero, fastMRI for reducing the time [...]
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
Expressive Real-time Intersection Scheduling: New Methods for Adaptive Traffic Signal Control
Abstract: Traffic congestion is a widespread problem throughout global metropolitan areas. In this thesis, we consider methods to optimize the performance of traffic signals to reduce congestion. We begin by presenting Expressive Real-time Intersection Scheduling (ERIS), a schedule-driven intersection control strategy that runs independently on each intersection in a traffic network. For each intersection, ERIS [...]
Carnegie Mellon University
Open-world 3D Object Detection
Abstract: Perception for autonomous robots presents a set of unique challenges: finding the right representation for 3D signals, adapting to an open-world setting, and exploiting geometric priors. Successfully detecting objects regardless of their labels lays a solid foundation for safe navigation. I will present two of my recent works in this line. First, I will [...]
Towards Weakly-Supervised Visual Understanding
Abstract: Learning with weak and self-supervisions recently emerged as compelling tools towards leveraging vast amounts of unlabeled or partially-labeled data. In this talk, I will present some of the latest advances in weakly-supervised visual scene understanding from NVIDIA. Specifically, I will summarize and discuss some challenges and potential solutions in weakly-supervised learning, and introduce our [...]
MSR Thesis Talk: Jenny Nan
Title: Combining Deep Learning and Verification for Precise Object Instance Detection Abstract: Deep learning based object detectors often return false positives with very high confidence. Although they optimize generic detection performance, such as mean average precision (mAP), they are not designed for reliability. For a reliable detection system, if a high confidence detection is [...]
Carnegie Mellon University
MSR Thesis talk – Vasu Agrawal
Title: Ground Up Design of a Multi-modal Object Localization System Abstract: Rapid situational awareness is the key to enabling a successful response from first responders during an emergency, where time is of the essence. Emergency personnel are often sent into incident scenes to gather information, but this is often a dangerous and slow process. Subterranean environments [...]
MSR Thesis Talk – Swaminathan Gurumurthy
Title: Improving generalization in data-driven models with task-specific knowledge Abstract: With the rise of the over-parameterized deep learning models and massive datasets, many have started advocating towards minimizing the amount of prior knowledge added to a learning model. Ironically, the traditional machine learning community advocated for exactly the opposite. Whereas the latter assumes knowledge of [...]
RI Winter Party
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.
Imaging without focusing: A computational approach to miniaturizing cameras
Abstract: Miniaturization of cameras is key to enabling new applications in areas such as connected devices, wearables, implantable medical devices, in vivo microscopy, and micro-robotics. Recently, lenses were identified as the main bottleneck in miniaturization of cameras. Standard smaller lens-system camera modules have a thickness of about 10 mm or higher, and reducing the size [...]
MRSD Annual Poster Presentation
Nine RI MRSD program student teams will use posters, videos, and hardware to show their project work on truck crash avoidance, balance recovery, construction via UAVs, room tidying, crop disease detection, beach cleaning, temperature field sensing, UGV-UAV firefighting, and multirover moon pit modeling. Website: https://mrsd.ri.cmu.edu/project-examples/student-project-websites/spring-2019-fall-2019/
Adaptive Planning and Control of Wheeled Mobile Robots in Challenging Environments
Abstract: Over the last two decades, we have seen driverless cars conquer the Mojave desert, drive on mars and operate on our streets and warehouses. One of the most fundamental requirements of such robots is their ability to navigate their environment with minimal human oversight. As more robots graduate from the confines of laboratories to [...]
Towards photo-realistic face digitization from monocular videos
Abstract: Recent advances in face capture now enable digitizing high-quality 3D faces for the entertainment industry. Standardized digitization solutions, however, require tailor-made capture systems and extensive manual work, making them expensive and hard to deploy. With the advent of commodity sensors, new lightweight approaches that push the boundaries of human digitization have been introduced, slowly [...]
When to use CNNs for Inverse Problems in Vision
Abstract: Reconstruction tasks in computer vision aim fundamentally to recover an undetermined signal from a set of noisy measurements. Examples include super-resolution, image denoising, and non-rigid structure from motion\cite{Kong_2019}, all of which have seen recent advancements through deep learning. However, earlier work made extensive use of sparse signal reconstruction frameworks (e.g. convolutional sparse coding). While [...]
Toward telelocomotion: human sensorimotor control of contact-rich robot dynamics
Abstract: Human interaction with the physical world is increasingly mediated by automation -- planes assist pilots, cars assist drivers, and robots assist surgeons. Such semi-autonomous machines will eventually pervade our world, doing dull and dirty work, assisting the elderly and disabled, and responding to disasters. Recent results (e.g. from the DARPA Robotics Challenge) demonstrate that, [...]
2020 RI Faculty Dinner
Invitation with information will be emailed to invitees.
Formal Synthesis for Robots
Abstract: In this talk I will describe how formal methods such as synthesis – automatically creating a system from a formal specification – can be leveraged to design robots, explain and provide guarantees for their behavior, and even identify skills they might be missing. I will discuss the benefits and challenges of synthesis techniques and [...]
Reconstructing 3D Human Avatars from Monocular Images
Abstract: Statistical 3D human body models have helped us to better understand human shape and motion and already enabled exciting new applications. However, if we want to learn detailed, personalized, and clothed models of human shape, motion, and dynamics, we require new approaches that learn from ubiquitous data such as plain RGB-images and video. I [...]
Carnegie Mellon University
Learning Dense 3D Object Reconstruction without Geometric Supervision
Abstract: Geometric alignment across visual data has been the fundamental issue for effective and efficient computer vision algorithms. The established pixel correspondences between images indirectly infer the underlying 3D geometry, physically or semantically. While this builds the foundation of classical multi-view 3D reconstruction algorithms such as Structure from Motion (SfM) and Simultaneous Localization and Mapping [...]
Extreme Motions in Biological and Engineered Systems
Abstract: Dr. Temel’s work mainly focuses on understanding the dynamics and energetics of extreme motions in small-scale natural and synthetic systems. Small-scale biological systems achieve extraordinary accelerations, speeds, and forces that can be repeated with minimal costs throughout the life of the organism. Zeynep uses analytical and computational models as well as physical prototypes to learn about these systems, test [...]
Reasoning about complex media from weak multi-modal supervision
Abstract: In a world of abundant information targeting multiple senses, and increasingly powerful media, we need new mechanisms to model content. Techniques for representing individual channels, such as visual data or textual data, have greatly improved, and some techniques exist to model the relationship between channels that are “mirror images” of each other and contain [...]