From the 1 of 7 linked papers with an AI index.
7 papers
Action Chunk Scheduling for Batched Robot Policy Serving
Rohan Bansal, David He, Nadun Ranawaka Arachchige +4
Deploying robot foundation models at scale is the next step towards realizing the potential of general-purpose robots. However, Vision-Language-Action (VLA) and other foundation mo…
Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation
Woo Chul Shin, Zhenyang Chen, Alfred Cueva +5
The paper presents Static In, Dynamic Out (SIDO), a method that augments static-object demonstrations with counterfactual actions to enable visuomotor policies to handle moving obj…
WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations
Zhenyang Chen, Chuizheng Kong, Chuye Zhang +4
Direct transfer from human demonstration to learnable robot action is a crucial step towards scalable whole-body mobile manipulation. While human data scales better than mobile tel…
A Closed-Form Geometric Retargeting Solver for Upper Body Humanoid Robot Teleoperation
Chuizheng Kong, Yunho Cho, Wonsuhk Jung +11
Retargeting human motion to robot poses is a practical approach for teleoperating bimanual humanoid robot arms, but existing methods can be suboptimal and slow, often causing undes…
Generalizable Domain Adaptation for Sim-and-Real Policy Co-Training
Shuo Cheng, Liqian Ma, Zhenyang Chen +3
Behavior cloning has shown promise for robot manipulation, but real-world demonstrations are costly to acquire at scale. While simulated data offers a scalable alternative, particu…
ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation
Yangcen Liu, Woo Chul Shin, Yunhai Han +3
Learning robot manipulation from abundant human videos offers a scalable alternative to costly robot-specific data collection. However, domain gaps across visual, morphological, an…