PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Motion planning for manipulation under pose uncertainty using contacts

NSH 4305

Abstract: Numerous manipulation tasks, such as plug insertion and pipe assembly, demand an extremely high level of precision in pose estimation. Even minor errors, on the order of 2mm, can lead to task failure. While robots often rely on vision for object detection and localization, achieving consistent, high-precision localization using visual methods is not always [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Optimal Modular Robot Design for Mobile Manipulation in Agriculture

NSH 3305

Abstract: Although agriculture is a highly mechanized industry, numerous sectors like horticulture and floriculture heavily depend on manual labor because they require safe handling of plants and produce that can only be left to humans. However, many research and commercial robots have succeeded in several challenging dexterous manipulation tasks like harvesting, pruning, and plant health [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Aligning Robot Task and Interaction Policies to Human Values

Abstract: The value alignment problem considers how robots can learn to behave in accordance with human values. Today, robot learning paradigms enable humans to provide data (e.g., preference labels or demonstrations), which the robot uses to update its behavior (e.g., reward model or policy) to be closer to the human’s values. However, the current paradigm [...]

PhD Thesis Proposal
PhD Student
Robotics Institute,
Carnegie Mellon University

Accelerating Robot Task Learning with Large Pretrained Models and Internet Data

NSH 3305

Abstract: Large pre-trained models and internet data sources are key to general and efficient robot task learning. However, learning contact-rich behaviors, semantic task constraints, and robust task planning from internet data sources remains an open challenge. This proposal seeks to make progress towards a general robot task learning system leveraging pre-trained models and internet data. [...]