PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards diverse zero-shot manipulation via actualizing visual plans

GHC 4405

Abstract: In this thesis, we seek to learn a generalizable goal-conditioned policy that enables zero-shot robot manipulation — interacting with unseen objects in novel scenes without test-time adaptation. Robots that can be reliably deployed out-of-the-box in new scenarios have the potential for helping humans in everyday tasks. Not requiring any test-time training through demonstrations or [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Deep Learning for Sensors: Development to Deployment

NSH 3305

Abstract: Robots rely heavily on sensing to reason about physical interactions, and recent advancements in rapid prototyping, MEMS sensing, and machine learning have led to a plethora of sensing alternatives. However, few of these sensors have gained widespread use among roboticists. This thesis proposes a framework for incorporating sensors into a robot learning paradigm, from [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Offline Learning for Stochastic Multi-Agent Planning in Autonomous Driving

GHC 4405

Abstract: Fully autonomous vehicles have the potential to greatly reduce vehicular accidents and revolutionize how people travel and how we transport goods. Many of the major challenges for autonomous driving systems emerge from the numerous traffic situations that require complex interactions with other agents. For the foreseeable future, autonomous vehicles will have to share the [...]

MSR Thesis Defense
MSR Student
Robotics Institute,
Carnegie Mellon University

Transfer Learning via Temporal Contrastive Learning Inbox

GHC 4405

Abstract: This thesis introduces a novel transfer learning framework for deep reinforcement learning. The approach automatically combines goal-conditioned policies with temporal contrastive learning to discover meaningful sub-goals. The approach involves pre-training a goal-conditioned agent, finetuning it on the target domain, and using contrastive learning to construct a planning graph that guides the agent via sub-goals. Experiments [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Towards Influence-Aware Safe Human-Robot Interaction

NSH 3305

Abstract: In recent years, we have seen through recommender systems on social media how influential (and potentially harmful) algorithms can be in our lives, sometimes creating polarization and conspiracies that lead to unsafe behavior. Now that robots are also growing more common in the real world, we must be very careful to ensure that they [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Learning to Manipulate beyond Imitation

NSH 3002

Abstract: Imitation learning has been a prevalent approach for teaching robots manipulation skills but still suffers from scalability and generalizability. In this talk, I'll argue for going beyond elementary behavioral imitation from human demonstrations. Instead, I'll present two key directions: 1) Creating Manipulation Controllers from Pre-Trained Representations, and 2) Representing Video Demonstrations with Parameterized Symbolic [...]

PhD Thesis Defense
Extern
Robotics Institute,
Carnegie Mellon University

Improving Robot Capabilities Through Reconfigurability

GHC 6501

Abstract: Advancements in robot capabilities are often achieved through integrating more hardware components. These hardware additions often lead to systems with high power consumption, fragility, and difficulties in control and maintenance. However, is this approach the only path to enhancing robot functionality? In this talk, I introduce the PuzzleBots, a modular multi-robot system with passive [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Design Principles for Robotics Systems that Support Human-Human Collaborative Learning

GHC 6121

Abstract: Robots possess unique affordances granted by combining software and hardware. Most existing research focuses on the impact of these affordances on human-robot collaboration, but the theory of how robots can facilitate human-human collaboration is underdeveloped. Such theory would be beneficial in education. An educational device can afford collaboration in both assembly and use. This [...]

PhD Speaking Qualifier
PhD Student
Robotics Institute,
Carnegie Mellon University

Leveraging Parallelism to Accelerate Quadratic Program Solvers for MPC

GHC 8102

Abstract: Many problems in robotics can be formulated as quadratic programs (QPs). In particular, model-predictive control problems often involve repeatedly solving QPs at very high rates (up to kilohertz). However, while other areas of robotics like machine learning have achieved high performance by taking advantage of parallelism on modern computing hardware, state-of-the-art algorithms for solving [...]