From the 1 of 16 linked papers with an AI index.
16 papers
Mixture of Frames Policy: Multi-Frame Action Denoising for Bimanual Mobile Manipulation
Dian Wang, Jisang Park, Xiaomeng Xu +3
The paper introduces Mixture of Frames Policy (MoF), a diffusion-based visuomotor controller that denoises actions simultaneously in several coordinate frames to better handle bima…
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…
From Prior to Pro: Efficient Skill Mastery via Distribution Contractive RL Finetuning
Zhanyi Sun, Shuran Song
We introduce Distribution Contractive Reinforcement Learning (DICE-RL), a framework that uses reinforcement learning (RL) as a "distribution contraction" operator to refine pretrai…
Robustness of Robotic Manipulation: Foundations and Frontiers
Yifei Dong, Zhanyi Sun, Lujie Yang +5
Humans and animals exhibit remarkable robustness in physical manipulation, yet robots remain far behind. Progress toward human-level manipulation robustness is hindered by the abse…
Behavior Prompting Policy: Demonstrations as Prompts for Manipulation
Austin Patel, Ben Pekarek, Joel Enrique Castro Hernandez +1
We study behavior prompting, a paradigm that enables robots to perform new tasks at inference time given a single human demonstration, which we call a behavior prompt. To enable th…
PanoVine: Whole-Body Visuomotor Control for Soft Growing Vine Robot
Yimeng Qin, Xiaomeng Xu, William Heap +3
Vine robots, a class of soft, growing robots, are suitable for navigating complex and confined environments due to their compliant bodies and self-supporting growth mechanism. Howe…