8 papers · 1 filter
MonoDuo: Using One Robot Arm to Learn Bimanual Policies
Sandeep Bajamahal, Lawrence Yunliang Chen, Toru Lin +3
Bimanual coordination is essential for many real-world manipulation tasks, yet learning bimanual robot policies is limited by the scarcity of bimanual robots and datasets. Single-a…
Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation
Jiahe Pan, Stelian Coros, Jitendra Malik +1
A primary bottleneck in contact-rich manipulation is the difficulty of collecting real-world data. Sim-to-real reinforcement learning offers a scalable alternative, but the simulat…
How to Peel with a Knife: Aligning Fine-Grained Manipulation with Human Preference
Toru Lin, Shuying Deng, Zhao-Heng Yin +2
Many essential manipulation tasks - such as food preparation, surgery, and craftsmanship - remain intractable for autonomous robots. These tasks are characterized not only by conta…
Coordinated Humanoid Manipulation with Choice Policies
Haozhi Qi, Yen-Jen Wang, Toru Lin +4
Humanoid robots hold great promise for operating in human-centric environments, yet achieving robust whole-body coordination across the head, hands, and legs remains a major challe…
Learning Dexterous Manipulation Skills from Imperfect Simulations
Elvis Hsieh, Wen-Han Hsieh, Yen-Jen Wang +4
Reinforcement learning and sim-to-real transfer have made significant progress in dexterous manipulation. However, progress remains limited by the difficulty of simulating complex…
Emergent Active Perception and Dexterity of Simulated Humanoids from Visual Reinforcement Learning
Zhengyi Luo, Chen Tessler, Toru Lin +8
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…