PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards Robotic Tree Manipulation: Leveraging Graph Representations

GHC 4405

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Tracking Any”Thing” in Videos

NSH 3001

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Customizing Large-scale Text-to-Image Models

NSH 4305

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) [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

How to Design Robotic Hands That Wield Tools

NSH 1305

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning Local Heuristics in Heuristic Search

NSH 3305

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Joint 2D and 3D Semi-Supervised Object Detection

NSH 4305

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards Agile Robotics: Creating Push-Off Skills for Dynamic Interactions

GHC 8102

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. [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Generative Evolutionary Search with Diffusion Models for Trajectory Optimization

NSH 4305

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Tartancalib: Iterative Wide-Angle Lens Calibration

GHC 8115

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 [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Zero-Shot Video Question Answering with Procedural Programs

GHC 6121

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, [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Robust Body Exposure (RoBE): A Graph-based Dynamics Modeling Approach to Manipulating Blankets over People

NSH 1109

Abstract: Robotic caregivers could potentially improve the quality of life of many who require physical assistance. However, in order to assist individuals who are lying in bed, robots must be capable of dealing with a significant obstacle: the blanket or sheet that will almost always cover the person's body. We propose a method for targeted [...]