25 citations · 34 across the 8 of their papers we have counts for
8 papers
Embodied Uncertainty-Aware Object Segmentation
Xiaolin Fang, Leslie Pack Kaelbling, Tomás Lozano-Pérez
We introduce uncertainty-aware object instance segmentation (UncOS) and demonstrate its usefulness for embodied interactive segmentation. To deal with uncertainty in robot percepti…
Learning Reusable Manipulation Strategies
Jiayuan Mao, Joshua B. Tenenbaum, Tomás Lozano-Pérez +1
Humans demonstrate an impressive ability to acquire and generalize manipulation "tricks." Even from a single demonstration, such as using soup ladles to reach for distant objects,…
Neural Relational Inference with Fast Modular Meta-learning
Ferran Alet, Erica Weng, Tomás Lozano Pérez +1
\textit{Graph neural networks} (GNNs) are effective models for many dynamical systems consisting of entities and relations. Although most GNN applications assume a single type of e…
Compositional Diffusion-Based Continuous Constraint Solvers
Zhutian Yang, Jiayuan Mao, Yilun Du +4
This paper introduces an approach for learning to solve continuous constraint satisfaction problems (CCSP) in robotic reasoning and planning. Previous methods primarily rely on han…
Learning Rational Subgoals from Demonstrations and Instructions
Zhezheng Luo, Jiayuan Mao, Jiajun Wu +3
We present a framework for learning useful subgoals that support efficient long-term planning to achieve novel goals. At the core of our framework is a collection of rational subgo…
Local Neural Descriptor Fields: Locally Conditioned Object Representations for Manipulation
Ethan Chun, Yilun Du, Anthony Simeonov +2
A robot operating in a household environment will see a wide range of unique and unfamiliar objects. While a system could train on many of these, it is infeasible to predict all th…