68 citations · 103 across the 8 of their papers we have counts for
8 papers · 1 filter
Best of Sim and Real: Decoupled Visuomotor Manipulation via Learning Control in Simulation and Perception in Real
Jialei Huang, Zhaoheng Yin, Yingdong Hu +3
Sim-to-real transfer remains a fundamental challenge in robot manipulation due to the entanglement of perception and control in end-to-end learning. We present a decoupled framewor…
Learning Generalizable Tool-use Skills through Trajectory Generation
Carl Qi, Yilin Wu, Lifan Yu +4
Autonomous systems that efficiently utilize tools can assist humans in completing many common tasks such as cooking and cleaning. However, current systems fall short of matching hu…
GELLO: A General, Low-Cost, and Intuitive Teleoperation Framework for Robot Manipulators
Philipp Wu, Yide Shentu, Zhongke Yi +2
Humans can teleoperate robots to accomplish complex manipulation tasks. Imitation learning has emerged as a powerful framework that leverages human teleoperated demonstrations to t…
SpawnNet: Learning Generalizable Visuomotor Skills from Pre-trained Networks
Xingyu Lin, John So, Sashwat Mahalingam +2
The existing internet-scale image and video datasets cover a wide range of everyday objects and tasks, bringing the potential of learning policies that generalize in diverse scenar…
Self-supervised Transparent Liquid Segmentation for Robotic Pouring
Gautham Narayan Narasimhan, Kai Zhang, Ben Eisner +2
Liquid state estimation is important for robotics tasks such as pouring; however, estimating the state of transparent liquids is a challenging problem. We propose a novel segmentat…
SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
Xingyu Lin, Yufei Wang, Jake Olkin +1
Manipulating deformable objects has long been a challenge in robotics due to its high dimensional state representation and complex dynamics. Recent success in deep reinforcement le…