Search Results for author: Toru Lin

Found 8 papers, 3 papers with code

Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning

no code implementations18 May 2025 Zhengyi Luo, Chen Tessler, Toru Lin, Ye Yuan, Tairan He, Wenli Xiao, Yunrong Guo, Gal Chechik, Kris Kitani, Linxi Fan, Yuke Zhu

Human behavior is fundamentally shaped by visual perception -- our ability to interact with the world depends on actively gathering relevant information and adapting our movements accordingly.

Object

Sim-to-Real Reinforcement Learning for Vision-Based Dexterous Manipulation on Humanoids

no code implementations27 Feb 2025 Toru Lin, Kartik Sachdev, Linxi Fan, Jitendra Malik, Yuke Zhu

This work investigates the key challenges in applying reinforcement learning to solve a collection of contact-rich manipulation tasks on a humanoid embodiment.

Contact-rich Manipulation reinforcement-learning +1

Learning Visuotactile Skills with Two Multifingered Hands

1 code implementation25 Apr 2024 Toru Lin, Yu Zhang, Qiyang Li, Haozhi Qi, Brent Yi, Sergey Levine, Jitendra Malik

Two significant challenges exist: the lack of an affordable and accessible teleoperation system suitable for a dual-arm setup with multifingered hands, and the scarcity of multifingered hand hardware equipped with touch sensing.

Twisting Lids Off with Two Hands

no code implementations4 Mar 2024 Toru Lin, Zhao-Heng Yin, Haozhi Qi, Pieter Abbeel, Jitendra Malik

Manipulating objects with two multi-fingered hands has been a long-standing challenge in robotics, due to the contact-rich nature of many manipulation tasks and the complexity inherent in coordinating a high-dimensional bimanual system.

Deep Reinforcement Learning reinforcement-learning +1

MIMEx: Intrinsic Rewards from Masked Input Modeling

1 code implementation NeurIPS 2023 Toru Lin, Allan Jabri

We show how this perspective naturally leads to a unified view on existing intrinsic reward approaches: they are special cases of conditional prediction, where the estimation of novelty can be seen as pseudo-likelihood estimation with different mask distributions.

Prediction

Visual Grounding of Learned Physical Models

1 code implementation ICML 2020 Yunzhu Li, Toru Lin, Kexin Yi, Daniel M. Bear, Daniel L. K. Yamins, Jiajun Wu, Joshua B. Tenenbaum, Antonio Torralba

The abilities to perform physical reasoning and to adapt to new environments, while intrinsic to humans, remain challenging to state-of-the-art computational models.

Visual Grounding

Model Based Planning with Energy Based Models

no code implementations15 Sep 2019 Yilun Du, Toru Lin, Igor Mordatch

We provide an online algorithm to train EBMs while interacting with the environment, and show that EBMs allow for significantly better online learning than corresponding feed-forward networks.

model Reinforcement Learning +1

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