Student Talks
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 [...]