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Multisensory Continual Learning: Adapting Pretrained Visuomotor Policies to Force
Jaden Clark, Changhao Wang, Yihuai Gao +5
Robot manipulation often relies on sensory feedback beyond vision, particularly in contact-rich settings where force, tactile, or audio signals reveal interaction states that are n…
Gated Memory Policy: In-Context Memorization and Adaptation
Yihuai Gao, Jeff Jinyun Liu, Shuang Li +1
Robotic manipulation tasks exhibit varying memory requirements, ranging from Markovian tasks that require no memory to non-Markovian tasks that demand in-context memorization of hi…
Unified Video Action Model
Shuang Li, Yihuai Gao, Dorsa Sadigh +1
A unified video and action model holds significant promise for robotics, where videos provide rich scene information for action prediction, and actions provide dynamics information…
TidyBot++: An Open-Source Holonomic Mobile Manipulator for Robot Learning
Jimmy Wu, William Chong, Robert Holmberg +6
Exploiting the promise of recent advances in imitation learning for mobile manipulation will require the collection of large numbers of human-guided demonstrations. This paper prop…
UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers
Huy Ha, Yihuai Gao, Zipeng Fu +2
We introduce UMI-on-Legs, a new framework that combines real-world and simulation data for quadruped manipulation systems. We scale task-centric data collection in the real world u…