4 papers
VQActFlow: Vector-Quantized Action Mode Steering for Multi-Task Robot Manipulation
Zhigen Zhao, Mark Leggiero, Yipu Chen +5
Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitatively different action modes fro…
WT-UMI: Tactile-based Whole-Body Manipulation via Force-Supervised Contact-Aware Planning
Jaehwi Jang, Zhaoyuan Gu, Alfred Cueva +15
Whole-body humanoid manipulation of bulky, deformable, and shared-load objects requires distributed contact sensing and explicit force regulation, yet most imitation policies treat…
Opt2Skill: Imitating Dynamically-feasible Whole-Body Trajectories for Versatile Humanoid Loco-Manipulation
Fukang Liu, Zhaoyuan Gu, Yilin Cai +8
Humanoid robots are designed to perform diverse loco-manipulation tasks. However, they face challenges due to their high-dimensional and unstable dynamics, as well as the complex c…
PPF: Pre-training and Preservative Fine-tuning of Humanoid Locomotion via Model-Assumption-based Regularization
Hyunyoung Jung, Zhaoyuan Gu, Ye Zhao +2
Humanoid locomotion is a challenging task due to its inherent complexity and high-dimensional dynamics, as well as the need to adapt to diverse and unpredictable environments. In t…