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Open-vocabulary Pick and Place via Patch-level Semantic Maps

We develop an approach for efficient open-vocabulary language-conditioned manipulation policy learning.

Sample Efficient Modeling of Drag Coefficients for Satellites with Symmetry

We study sample-efficient modeling of invariant drag coefficients with equivariant networks.

Language Conditioned Equivariant Grasp

We study how to ground language for robotic grasping while preserve the geometric structure of its symmetry.

Can Euclidean Symmetry Help in Reinforcement Learning and Planning?

We study whether Euclidean symmetry can help in reinforcement learning and planning, which models the geometric transformations between reference frames of robots.

Model-based Navigation in Environments with Novel Layouts Using Abstract 2-D Maps

This work aims to improve the zero-shot generalization performance in map-based navigation on novel layouts.

InterFact: Towards Interactive Factorization of Actionable Entities

This work proposes a reinforcement learning framework for compositional object-oriented environments.