PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Continual Learning of Compositional Skills for Robust Robot Manipulation

GHC 6501

Abstract: Real world robots need to continuously learn new manipulation tasks in a lifelong learning manner. These new tasks often share many sub-structures e.g. sub-tasks, controllers, preconditions, with previously learned tasks. To utilize these shared sub-structures, we explore a compositional and object-centric approach to learn manipulation tasks. The first part of this thesis focuses on [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Watch, Practice, Improve: Towards In-the-wild Manipulation

GHC 4405

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 [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Combining Physics-Based Light Transport and Neural Fields for Robust Inverse Rendering

NSH 3305

Abstract:   Inverse rendering — the process of recovering shape, material, and/or lighting of an object or environment from a set of images — is essential for applications in robotics and elsewhere, from AR/VR to perception on self-driving vehicles. While it is possible to perform inverse rendering from color images alone, it is often far easier [...]

PhD Thesis Defense
Extern
Robotics Institute,
Carnegie Mellon University

Improving the Transparency of Agent Decision Making to Humans Using Demonstrations

GHC 4405

Abstract: For intelligent agents (e.g. robots) to be seamlessly integrated into human society, humans must be able to understand their decision making. For example, the decision making of autonomous cars must be clear to the engineers certifying their safety, passengers riding them, and nearby drivers negotiating the road simultaneously. As an agent's decision making depends [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Robotic Climbing for Extreme Terrain Exploration

NSH 3305

Abstract: Climbing robots can operate in steep and unstructured environments that are inaccessible to other ground robots, with applications ranging from the inspection of artificial structures on Earth to the exploration of natural terrain features throughout the solar system. Climbing robots for planetary exploration face many challenges to deployment, including mass restrictions, irregular surface features, [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Perception amidst interaction: spatial AI with vision and touch for robot manipulation

GHC 6501

Abstract: Robots currently lack the cognition to replicate even a fraction of the tasks humans do, a trend summarized by Moravec's Paradox. Humans effortlessly combine their senses for everyday interactions—we can rummage through our pockets in search of our keys, and deftly insert them to unlock our front door. Before robots can demonstrate such dexterity, [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

[MSR Thesis Talk] SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM

3305 Newell-Simon Hall

Abstract: Dense simultaneous localization and mapping (SLAM) is crucial for numerous robotic and augmented reality applications. However, current methods are often hampered by the non-volumetric or implicit way they represent a scene. This talk introduces SplaTAM, an approach that leverages explicit volumetric representations, i.e., 3D Gaussians, to enable high-fidelity reconstruction from a single unposed RGB-D [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Human Perception of Robot Failure and Explanation During a Pick-and-Place Task

GHC 4405

Abstract: In recent years, researchers have extensively used non-verbal gestures, such as head and arm movements, to express the robot's intentions and capabilities to humans. Inspired by past research, we investigated how different explanation modalities can aid human understanding and perception of how robots communicate failures and provide explanations during block pick-and-place tasks. Through an in-person [...]

MSR Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning Distributional Models for Relative Placement

GHC 6121

Abstract: Relative placement tasks are an important category of tasks in which one object needs to be placed in a desired pose relative to another object.  Previous work has shown success in learning relative placement tasks from just a small number of demonstrations, when using relational reasoning networks with geometric inductive biases. However, such methods fail [...]

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 [...]