Learning to Manipulate Object Collections Using Grounded State Representations

17 September 2019

Papers citing "Learning to Manipulate Object Collections Using Grounded State Representations"

8 / 8 papers shown

Title
Latent Space Planning for Multi-Object Manipulation with Environment-Aware Relational Classifiers Yixuan Huang Nichols Crawford Taylor Adam Conkey Weiyu Liu Tucker Hermans 36 7 0 18 May 2023
Planning for Multi-Object Manipulation with Graph Neural Network Relational Classifiers Yixuan Huang Adam Conkey Tucker Hermans 17 26 0 24 Sep 2022
StructFormer: Learning Spatial Structure for Language-Guided Semantic Rearrangement of Novel Objects Weiyu Liu Chris Paxton Tucker Hermans D. Fox 35 91 0 19 Oct 2021
Predicting Stable Configurations for Semantic Placement of Novel Objects Chris Paxton Christopher Xie Tucker Hermans D. Fox 36 47 0 26 Aug 2021
Deep Visual Reasoning: Learning to Predict Action Sequences for Task and Motion Planning from an Initial Scene Image Danny Driess Jung-Su Ha Marc Toussaint LRM 13 100 0 09 Jun 2020
The Surprising Effectiveness of Linear Models for Visual Foresight in Object Pile Manipulation H. Suh Russ Tedrake 21 60 0 21 Feb 2020
CAD2RL: Real Single-Image Flight without a Single Real Image Fereshteh Sadeghi Sergey Levine SSL 234 809 0 13 Nov 2016
Modular Deep Q Networks for Sim-to-real Transfer of Visuo-motor Policies Fangyi Zhang Jurgen Leitner Michael Milford Peter Corke 34 39 0 21 Oct 2016