Search Results for author: Mengyuan Yan

Found 9 papers, 3 papers with code

Jump-Start Reinforcement Learning

no code implementations5 Apr 2022 Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman

In addition, we provide an upper bound on the sample complexity of JSRL and show that with the help of a guide-policy, one can improve the sample complexity for non-optimism exploration methods from exponential in horizon to polynomial.

reinforcement-learning

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

no code implementations4 Apr 2022 Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

We show how low-level skills can be combined with large language models so that the language model provides high-level knowledge about the procedures for performing complex and temporally-extended instructions, while value functions associated with these skills provide the grounding necessary to connect this knowledge to a particular physical environment.

Decision Making Language Modelling

GRAC: Self-Guided and Self-Regularized Actor-Critic

1 code implementation18 Sep 2020 Lin Shao, Yifan You, Mengyuan Yan, Qingyun Sun, Jeannette Bohg

One dominant component of recent deep reinforcement learning algorithms is the target network which mitigates the divergence when learning the Q function.

Decision Making OpenAI Gym +1

How to Close Sim-Real Gap? Transfer with Segmentation!

no code implementations14 May 2020 Mengyuan Yan, Qingyun Sun, Iuri Frosio, Stephen Tyree, Jan Kautz

Combining the control policy learned from simulation with the perception model, we achieve an impressive $\bf{88\%}$ success rate in grasping a tiny sphere with a real robot.

Robotics

Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects

no code implementations14 Nov 2019 Mengyuan Yan, Yilin Zhu, Ning Jin, Jeannette Bohg

Challenges in taking the state-space approach are the estimation of the high-dimensional state of a deformable object from raw images, where annotations are very expensive on real data, and finding a dynamics model that is both accurate, generalizable, and efficient to compute.

Self-Supervised Learning

Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping

no code implementations15 Apr 2019 Mengyuan Yan, Adrian Li, Mrinal Kalakrishnan, Peter Pastor

Our actor model reduces the inference time by 3 times compared to the state-of-the-art CEM method.

Robotic Grasping

Volumetric and Multi-View CNNs for Object Classification on 3D Data

2 code implementations CVPR 2016 Charles R. Qi, Hao Su, Matthias Niessner, Angela Dai, Mengyuan Yan, Leonidas J. Guibas

Empirical results from these two types of CNNs exhibit a large gap, indicating that existing volumetric CNN architectures and approaches are unable to fully exploit the power of 3D representations.

3D Object Recognition 3D Point Cloud Classification +1

3D Reconstruction from Full-view Fisheye Camera

no code implementations20 Jun 2015 Chuiwen Ma, Liang Shi, Hanlu Huang, Mengyuan Yan

In this report, we proposed a 3D reconstruction method for the full-view fisheye camera.

3D Reconstruction

Cannot find the paper you are looking for? You can Submit a new open access paper.