4 papers · 1 filter
DexFuture: Hierarchical Future-State Visuomotor Targeting for Bimanual Dexterous Tool Use
Runfa Blark Li, Kuang-Ting Tu, Nikola Raicevic +6
Bimanual dexterous tool use remains challenging for robots due to high-dimensional hand configurations and complex hand-tool-object dynamics and contact. Most existing control poli…
Rainbow-DemoRL: Combining Improvements in Demonstration-Augmented Reinforcement Learning
Dwait Bhatt, Shih-Chieh Chou, Nikolay Atanasov
Several approaches have been proposed to improve the sample efficiency of online reinforcement learning (RL) by leveraging demonstrations collected offline. The offline data can be…
Seeing the Bigger Picture: 3D Latent Mapping for Mobile Manipulation Policy Learning
Sunghwan Kim, Woojeh Chung, Zhirui Dai +5
In this paper, we demonstrate that mobile manipulation policies utilizing a 3D latent map achieve stronger spatial and temporal reasoning than policies relying solely on images. We…
PhysGraph: Physically-Grounded Graph-Transformer Policies for Bimanual Dexterous Hand-Tool-Object Manipulation
Runfa Blark Li, David Kim, Xinshuang Liu +7
Bimanual dexterous manipulation for tool use remains a formidable challenge in robotics due to the high-dimensional state space and complicated contact dynamics. Existing methods n…