Student Talks
MSR Thesis Talk: Heng Yu
Title: Towards Real-time Controllable Neural Face Avatars Abstract: Neural Radiance Fields (NeRF) are compelling techniques for modeling dynamic 3D scenes from 2D image collections. These volumetric representations would be well suited for synthesizing novel facial expressions but for three problems. First, deformable NeRFs are object agnostic and model holistic movement of the scene: they can [...]
MSR Thesis Talk: Winnie Kuang
Title: Design and Integration of Semantic Mapping System for Forest Fire Mitigation Abstract: Remote sensing technologies can provide an automated approach to monitor and analyze conditions in the forest environment over a period of time for forest maintenance and wildfire mitigation efforts. In particular, unmanned aerial vehicles (UAVs) are a promising remote sensing modality since they [...]
MSR Thesis Talk: Jinqi Luo
Title: Vision Model Diagnosis: A Generative Perspective Abstract: In the evolving landscape of computer vision, deep learning has emerged as a transformative force, enhancing a myriad of societal facets. The real-world deployment of such a deep vision model requires a reliable evaluation, particularly when the model can have different sensitivities across various semantic attributes and concepts. [...]
MSR Thesis Talk: Daphne Chen
Title: Learning Task Preferences from Real-World Data Abstract: In order to provide personalized assistance that is capable of adapting to the needs of unique individuals, it is necessary to understand peoples’ preferences for different tasks. Robot assistance often assumes a static model of the individual, while in the real world, people have different capabilities and needs [...]
Unified Control for Over and Fully-Actuated Aerial Vehicles
Abstract: The growing domain of aerial robotics necessitates advancements in the control strategies and robustness of over-actuated and fully-actuated aerial vehicles. This thesis proposal makes contributions to this endeavor by providing in-depth analysis and methodologies concerning these vehicles, control allocation strategies during actuator failures, high-fidelity simulations, and a unified control framework. Our completed work has [...]
MSR Thesis Talk: Prasanna Kettavarapalyam Sriganesh
Title: Fast Staircase Detection and Estimation with Multi-View Merging for Multi-Robot Systems Abstract: When robotic systems are deployed in the real world, they demand advanced mobility capabilities to operate in complex, three-dimensional environments designed for human use, e.g., multi-level buildings. Staircases have been an integral part of facilitating vertical movement in these three-dimensional environments. This work [...]
MSR Thesis Talk: Aarush Gupta
Title: LightSpeed: Light and Fast Neural Light Fields on Mobile Devices Abstract: Real-time novel-view image synthesis on mobile devices is prohibitive due to limited on-device computational power and storage. Using volumetric rendering methods, such as NeRF and its derivatives, on mobile devices is not suitable due to the high computational cost of volumetric rendering. On the [...]
MSR Thesis Talk: Akshaya Kesarimangalam Srinivasan
Title: Multi-agent Multi-objective Ergodic Search Abstract: In order to find points of interest in a given domain, many planners use a priori information to guide the search to expedite the detection of targets. We present an approach to direct multiple agents (MA) to search a given domain subject to multiple objectives (MO), each characterized by its own information [...]
MSR Thesis Talk: Joshua Spisak
Title: Stochastic Optimization for Autonomous Navigation, Leveraging Parallel Computation Abstract: Stochastic Optimal Control (SOC) is a framework that allows disturbances and uncertainty in system models to be accounted for in its optimization framework. Despite accounting for this uncertainty, many first and second order methods for solving SOC problems are subject to local minima and are [...]
MSR Thesis Talk: Xuxin Cheng
Title: Learning Legged Robot Agility: Sim-to-Real and Beyond Abstract: Legged robotics has seen significant advancements in both manipulation and locomotion. However, there remain significant gaps compared to their biological counterparts, particularly in energy efficiency, natural motion, and the capacity for agile skills. This thesis primarily focuses on two aspects: the unified control of legged manipulators [...]
MSR Thesis Talk: Harry Freeman
Title: Computer Vision-Based Phenotyping in Agriculture: Leveraging Semantic Information for Non-Destructive Small Crop Analysis Abstract: Fast and reliable non-destructive phenotyping of plants plays an important role in precision agriculture, as the information enables farmers to make real-time crop management decisions without affecting yield. To non-destructively phenotype crops, computer and stereo-vision based methods are commonly used, [...]
MSR Thesis Talk: Nishant Mohanty
Title: Multi-Robot Control using Control Barrier Functions: Theory and Application Abstract: Control Barrier Functions (CBFs) have emerged as a powerful theoretical tool for designing controllers with provable safety guarantees. This work presents a novel methodology that leverages CBFs to synthesize controllers for multi-robot coordination. Two multi-agent use cases are explored, i.e., a) Non-Cooperative Herding and [...]
MSR Thesis Talk: Yuyao Shi
Title: A Learning Approach to Understand How Spinal Cord Learns Multiple Behaviors Abstract: The spinal cord plays a crucial role in the control of human locomotion, generating motor patterns and coordinating reflex responses to sensory signals. Although this spinal control is traditionally viewed as a simple relay system, more recent neurophysiological evidence points to a [...]
Carnegie Mellon University
MSR Thesis Talk: FNU Abhimanyu
Title: Improving Robotic Ultrasound AI Using Optical Flow Abstract: Ultrasound is an important modality for medical intervention such as vascular access because it is safe, portable, and low-cost. However, ultrasound scanning requires trained sonographers who are scarce, and it can be challenging to perform ultrasound examinations in disaster or battlefield scenarios. This motivates us to automate [...]
Vision-based Proprioceptive and Tactile Sensing for Soft Robots
Abstract: Soft robotic manipulators present many unique advantages in difficult manipulation tasks. The inherent compliance of soft robots' constituent deformable material makes them safe and reliable in delicate tasks such as harvesting fruit and assisting in household work. To address challenges in proprioceptive and tactile sensing for soft robots, we present a family of vision-based [...]
MSR Thesis Talk: Lucas Casanova De Oliveira Nogueira
Title: SuperLoop: a LIDAR-based SLAM Back-end for Underground Exploration Abstract: Robots deployed in underground scenarios require a SLAM system that can handle a variety of challenges, such as the absence of GPS, large scale maps, bad illumination, and geometrically degenerate environments. It is nearly impossible for any SLAM solution to handle all these challenges perfectly, specially [...]
Learning via Visual-Tactile Interaction
Abstract: Humans learn by interacting with their surroundings using all of their senses. The first of these senses to develop is touch, and it is the first way that young humans explore their environment, learn about objects, and tune their cost functions (via pain or treats). Yet, robots are often denied this highly informative and [...]
MSR Thesis Talk: Neil Khera
Title: PyCubed-Mini: A Low-Cost, Open-Source Satellite Research Platform Abstract: Satellite development has become more accessible with decreasing launch costs and shrinking hardware. However, the expenses associated with pre-built satellite kits remain high, making it difficult for student and hobbyist teams to participate. The lack of standardized satellite hardware and software further adds to the challenge, [...]
Strategy assessment for solving rich physical problems
Abstract: We present a framework that acts as an "intuitive physics reasoner" which takes in strategies expressed in natural language (whether from a human or LLM), and assesses their validity based on a physics knowledge library. We believe the ability to quickly determine whether a strategy is worth considering and allocating further resources to planning [...]
MSR Thesis Talk: Siva Kailas
Title: Multi-Robot Information Gathering for Spatiotemporal Environment Modelling Abstract: Learning to predict or forecast spatiotemporal (ST) environmental processes from a sparse set of samples collected autonomously is a difficult task from both a sampling perspective (collecting the best sparse samples) and from a learning perspective (predicting unseen locations or forecasting the next timestep). We investigate [...]
MRS Thesis Talk: Ruijie Fu
Title: Towards Mechanical Communication in Multi-Agent Locomotive Systems: Principally Kinematic Robots on a Shared Platform Abstract: Many biological multi-agent systems exhibit a mechanism for information exchange among individuals known as mechanical communication, which leads to the emergence of collective behavior within the group. One such example is the swarming behavior of bacteria, where they form rafts [...]
Personalized Context-aware Affective Nonverbal Robot Feedback
Abstract: We first consider the problem of estimating context, specifically key features of the human state. We predict engagement-related events in an educational activity before the end of that activity, which could allow the robot to provide feedback early enough to improve the human's experience. We then explore generating nonverbal affective robot behavior by correlating [...]
Redefining the Perception-Action Interface: Visual Action Representations for Contact-Centric Manipulation
Abstract: In robotics, understanding the link between perception and action is pivotal. Typically, perception systems process sensory data into state representations like segmentations and bounding boxes, which a planner uses to plan actions. However, this state estimation approach can fail in environments with partial observability, and in cases with challenging object properties like transparency and deformability. [...]
Architecture and Algorithms for Space-Based Global Wildlife Tracking
Abstract: Accurate satellite based positioning revolutionized several industries over the past two decades from agriculture to transportation. However, conventional GNSS receivers consume significant amounts of energy and are too large for many applications, including wildlife-tracking which is critical for conservation efforts and improving our understanding of the global climate. To address this capability gap, we [...]
Multi-Human 3D Reconstruction from Monocular Videos
Abstract: We study the problem of multi-human 3D reconstruction from videos captured in the wild. Human movements are dynamic, and accurately reconstructing them in various settings is crucial for developing immersive social telepresence, assistive humanoid robots, and augmented reality systems. However, creating such a system requires addressing fundamental issues with previous works regarding the data [...]
Language-Conditioned Object Detection and Manipulation
Abstract: Traditional object detection methods are often confined to predefined object vocabularies, limiting their versatility in real-world scenarios where robots need to understand and execute diverse household tasks. Additionally, the 2D and 3D perception communities have typically pursued separate approaches tailored to their respective domains. In this thesis, we present a language-conditioned object detector with [...]
How I Learned to Love Blobs: The Power of Gaussian Representations in Differentiable Rendering and Optimization
Abstract: In this thesis, we explore the use of Gaussian Representations in multiple application areas of computer vision and robotics. In particular, we design a ray-based differentiable renderer for 3D Gaussians that can be used to solve multiple classic computer vision problems in a unified manner. For example, we can reconstruct 3D shapes from color, [...]
Watch, Practice, Improve: Towards In-the-wild Manipulation
Abstract: The longstanding dream of many roboticists is to see robots perform diverse tasks in diverse environments. To build such a robot that can operate anywhere, many methods train on robotic interaction data. While these approaches have led to significant advances, they rely on heavily engineered setups or high amounts of supervision, neither of which [...]
Towards Photorealistic Dynamic Capture and Animation of Human Hair and Head
Abstract: Realistic human avatars play a key role in immersive virtual telepresence. To reach a high level of realism, a human avatar needs to faithfully reflect human appearance. A human avatar should also be drivable and express natural motions. Existing works have made significant progress in building drivable realistic face avatars, but they rarely include [...]
Modeling Dynamic Clothing for Data-Driven Photorealistic Avatars
Abstract: In this thesis, we aim to build photorealistic animatable avatars of humans wearing complex clothing in a data-driven manner. Such avatars will be a critical technology to enable future applications such as immersive telepresence in Virtual Reality (VR) and Augmented Reality (AR). Existing full-body avatars that jointly model geometry and view-dependent texture using Variational [...]
Manipulation Among Movable Objects for Pick-and-Place Tasks in Cluttered 3D Workspaces
Abstract: In cluttered real-world workspaces, simple pick-and-place tasks for robot manipulators can be quite challenging to solve. Often there is no collision-free trajectory that allows the robot to grasp and extract a desired object from the scene. This requires motion planning algorithms to reason about rearranging some of the “movable” clutter in the scene so [...]
Generalizable Dexterity with Reinforcement Learning
Abstract: Dexterity, the ability to perform complex interactions with the physical world, is at the core of robotics. However, existing research in robot manipulation has been focused on tasks that involve limited dexterity, such as pick-and-place. The motor skills of the robots are often quasi-static, have a predefined or limited sequence of contact events, and [...]
Preference Based Optimization of Multi-Objective Robot Performance
Abstract: Robotic systems often require that tradeoffs be made--for example, between performance and robustness, power and longevity, or efficiency and safety. While roboticists can design cost functions with hand-picked weights for different metrics, it is not always a straightforward task, particularly when some aspects of performance are not easily quantified. This can occur especially when [...]
Ensuring safety for uncertain high-dimensional robotic systems
Abstract: Two major obstacles for safe control and planning are (1) scaling to high-dimensional systems and (2) handling uncertain systems. This is problematic because such systems are ubiquitous in practice: e.g. drones with unknown drag, manipulators carrying unknown packages. In this proposal, we aim to address both challenges. At the control level, we have synthesized [...]
Trustworthy Learning using Uncertain Interpretation of Data
Abstract: Non-parametric models are popular in real-world applications of machine learning. However, many modern ML methods that ensure that models are pragmatic, safe, robust, fair, and otherwise trustworthy in increasingly critical applications, assume parametric, differentiable models. We show that, by interpreting data as locally uncertain, we can achieve many of these without being limited to [...]
Allocation, Planning, and Control in Off-road Automated Convoy Operations
Abstract: The lack of structure in off-road terrains makes off-road operations of automated platforms difficult. The difficulty arises from uncertainty in the optimality and safety of the actions (e.g., planning and control) taken by the automated platform. When multiple automated platforms are required to act in a coordinated manner (e.g., a convoy) in complex cluttered [...]
Robot Learning for Assistive Dressing
Abstract: Robot-assisted dressing could benefit the lives of many people such as older adults and individuals with disabilities. In this talk, I will present two pieces of work that use robot learning for this assistive task. In the first half of the talk, I will present our work on developing a robot-assisted dressing system that [...]
Towards Robotic Tree Manipulation: Leveraging Graph Representations
Abstract: There is growing interest in automating agricultural tasks that require intricate and precise interaction with specialty crops, such as trees and vines. However, developing robotic solutions for crop manipulation remains a difficult challenge due to complexities involved in modeling their deformable behavior. In this study, we present a framework for learning the deformation behavior [...]
Tracking Any”Thing” in Videos
Abstract: Being able to track anything is one of the fundamental steps to parse and understand a video. In this talk, I will present two pieces of work that tackle this problem at different spatial granularities. In the first half of the talk, I will discuss tracking any video pixel or particle through time in [...]
Exploring Diverse Interaction Types for Human in the Loop Robot Learning
Abstract: Teaching sessions between humans and robots will need to be maximally informative for optimal robot learning and to ease the human’s teaching burden. However, the bulk of prior work considers one or two modalities through which a human can convey information to a robot—namely, kinesthetic demonstrations and preference queries. Moreover, people will teach robots [...]
Learning Generalizable Robot Skills for Dynamic and Interactive Tasks
Abstract: Enabling robots to perform complex dynamic tasks such as picking up an object in one sweeping motion or pushing off a wall to quickly turn a corner is a challenging problem. The dynamic interactions implicit in these tasks are critical for successful task execution. Furthermore, given the interactive nature of such tasks, safety, in [...]
Customizing Large-scale Text-to-Image Models
Abstract: Advancements in large-scale generative models represent a watershed moment. These models can generate a wide variety of objects and scenes with different styles and compositions. However, these models are trained on a fixed snapshot of available data and often contain copyrighted or private images. This assumption makes them lacking in two aspects – (a) [...]
Building Robot Hands and Teaching Dexterity
Abstract: Our shared dream is to have robot humanoids with hands complete similar tasks that humans do. While there are a few robot hands available today, the popular opinion is that they are difficult to use, expensive, and hard to obtain which precludes their ubiquitous usage. We argue that this is not an inherent problem [...]
How to Design Robotic Hands That Wield Tools
Abstract: Tool manipulation is an essential human skill. It extends our manipulation capability beyond the capability of the biological hand, and is a defining feature of many important jobs centered on physical interaction with the real world. Yet, wielding a tool is drastically different from generally grasping an object. The prime examples are pens and [...]
Learning Local Heuristics in Heuristic Search
Abstract: Motion planning is a fundamental problem in robotics; how can we move robots efficiently and safely? Motion planning can be solved using several paradigms with their own strengths and weaknesses. This talk dives into Heuristic Graph Search and its application to motion planning by converting it to a problem of finding a start-goal path [...]
Low-Cost Multimodal Sensing and Dexterity for Deformable Object Manipulation
Abstract: To integrate robots seamlessly into daily life, they must be able to handle a variety of tasks in diverse environments, like assisting in hospitals or cooking in kitchens. Many of the items in these environments are deformable such as bedding in hospitals or vegetables in kitchens, and a certain level of dexterity is necessary [...]
Joint 2D and 3D Semi-Supervised Object Detection
Abstract: While numerous 3D detection works leverage the complementary relationship between RGB images and point clouds, developments in the broader framework of semi-supervised object recognition remain uninfluenced by multi-modal fusion. Current methods develop independent pipelines for 2D and 3D semi-supervised learning despite the availability of paired image and point cloud frames. Observing that the distinct [...]
New Methods for Satellite Control
Abstract: Since 2003, the number of satellites launched into orbit has grown from 100 per year to over 2000 per year. Over that same timeframe, incredible advances have been made in control systems for terrestrial robotics and autonomy. Despite the increased quantity of satellites in orbit and the advances made in terrestrial control systems, satellite [...]
[MSR Thesis Talk] Development and Testing of a Software Stack for an Autonomous Racing Vehicle
Abstract: Autonomous racing aims to replicate the human racecar driver with software and sensors. As in traditional motorsports, Autonomous Racing Vehicles (ARVs) are pushed to their dynamic limits in multi-agent scenarios at high (>= 100mph) speeds. This Operational Design Domain (ODD) presents unique challenges across the autonomy stack. The Indy Autonomous Challenge (IAC) is an [...]
[MSR Thesis Talk] Kitchen Robot Case Studies: Learning Manipulation Tasks from Human Video Demonstrations
Abstract: The vision of integrating a robot into the kitchen, capable of acting as a chef, remains a sought-after goal in robotics. Current robotic systems, mostly programmed for specific tasks, fall short in versatility and adaptability to a diverse culinary environment. While significant progress has been made in robotic learning, with advancements in behavior cloning, [...]
Towards Agile Robotics: Creating Push-Off Skills for Dynamic Interactions
Abstract: Dynamic interactions play a fundamental role in human capabilities, enabling us to achieve a wide range of tasks such as moving heavy objects, manipulating our surroundings, and changing directions rapidly and safely. In contrast, most conventional robotic systems lack this level of agility and cannot perform dynamic interactions, limiting their potential in practical applications. [...]
Learning Safe Human-Robot Interactions for a Seamlessly Shared Airspace
Abstract: The growing need for fully autonomous aerial operations in shared spaces, necessitates the development of reliable agents capable of navigating safely and seamlessly alongside uncertain human agents. In response, we advocate endowing autonomous agents with the ability to predict human actions, comprehend and ground abstract rules in the action space, and embrace the uncertainty [...]
Generative Evolutionary Search with Diffusion Models for Trajectory Optimization
Abstract: Diffusion models excel at modeling complex and multimodal trajectory distributions for decision-making and control. Reward-gradient guided denoising has been recently proposed to generate trajectories that maximize both a differentiable reward function and the likelihood under the data distribution captured by a diffusion model. Reward-gradient guided denoising requires a differentiable reward function fitted to both [...]
Tartancalib: Iterative Wide-Angle Lens Calibration
Abstract: Mobile vision systems greatly benefit from the large field-of-view enabled by wide-angle lenses. Accurate and robust intrinsic calibration is a critical prerequisite for leveraging this property. Calibrating wide-angle lenses with current state-of-the-art techniques yields poor results due to extreme distortion at the edge. In this work, we present TartanCalib, an accurate and robust method [...]
Sample-Efficient Reinforcement Learning with applications in Nuclear Fusion
Abstract: In many practical applications of reinforcement learning (RL), it is expensive to observe state transitions from the environment. In the problem of plasma control for nuclear fusion, the motivating example of this thesis, determining the next state for a given state-action pair requires querying an expensive transition function which can lead to many hours [...]
[MSR Thesis Talk] Neural Implicit Representations for Medical Ultrasound Volumes and 3D Anatomy-specific Reconstructions
Abstract: Most Robotic Ultrasound Systems (RUSs) equipped with ultrasound-interpreting algorithms rely on building 3D reconstructions of the entire scanned region or specific anatomies. These 3D reconstructions are typically created via methods that compound or stack 2D tomographic ultrasound images using known poses of the ultrasound transducer with the latter requiring 2D or 3D segmentation. While fast, this class [...]
Social Navigation with Pedestrian Groups
Abstract: Autonomous navigation in human crowds (i.e., social navigation) presents several challenges: The robot often needs to rely on its noisy sensors to identify and localize pedestrians in human crowds; the robot needs to plan efficient paths to reach its goals; the robot needs to do so in a safe and socially appropriate manner. Recent [...]
Zero-Shot Video Question Answering with Procedural Programs
Abstract: We propose to answer zero-shot questions about videos by generating short procedural programs that derive a final answer from solving a sequence of visual subtasks. We present Procedural Video Querying (ProViQ), which uses a large language model to generate such programs from an input question and an API of visual modules in the prompt, [...]
[MSR Thesis Talk] Enhancing RHex Robot Performance with Innovative Bioplastic Legs Responsive to Humidity
Abstract: Designing and developing robots that can effectively navigate real-world environments poses a significant challenge. To overcome this, many robotic systems draw inspiration from the adaptive behaviors of animals, which have evolved to thrive in diverse surroundings. Amphibious animals, for instance, seamlessly transition between walking and swimming, optimizing their locomotion efficiency based on environmental cues. [...]
Informative Path Planning Toward Autonomous Real-World Applications
Abstract: Gathering information from the physical world plays a crucial role in many applications—whether it be scientific research, environmental monitoring, search and rescue, defense, or disaster response. The utilization of robots for information gathering allows for the leveraging of intelligent algorithms to efficiently collect data, providing critical insights and facilitating informed decision-making. These autonomous robots [...]