PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Enabling Reliable Model-Based Planning with Inaccurate Models

GHC 8102

Abstract: This thesis aims to provide a framework for combining complementary tools that enable robots to manipulate objects in the world using diverse forms of knowledge. We consider heterogeneous types of knowledge, such as physics-based models, learned dynamics models, and model-free skills learned from human demonstrations. Each form of knowledge comes with its own assumptions [...]

PhD Thesis Defense
PhD Student
Robotics Institute,
Carnegie Mellon University

Unlocking Generalization for Robotics via Scale and Modularity

GHC 4405

Abstract: How can we build generalist robot systems? Looking at fields such as vision and language, the common theme has been large scale end-to-end learning with massive, curated datasets. In robotics, on the other hand, scale alone may not be enough due to the significant multimodality of robotics tasks, lack of easily accessible data and [...]