4 citations · 8 across the 23 of their papers we have counts for
8 papers · 1 filter
ViTacWorld: Scaling Visuo-Tactile World Models for Contact-Rich Robot Manipulation
Yunao Huang, Shiyu Sang, Haotao Lu +5
Contact-rich robot manipulation requires physical interaction cues that are often invisible to cameras, making tactile sensing essential for robust control. However, scaling visuo-…
TactiDex: A Real-World Tactile-Guided Benchmark for Human-Like Dexterous Manipulation
Suting Ni, Hanbing Zhang, Zhenyu Wei +4
Tactile feedback is fundamental to Hand-Object Interaction (HOI), governing contact formation, force regulation, and stable manipulation, making it essential for achieving true hum…
Steering Generative Reinforcement Learning into Stable Robotic Controller
Yixuan Wang, Shutong Ding, Ke Hu +3
Diffusion and flow-based generative policies provide a powerful policy class for reinforcement learning by inducing rich stochastic exploration through iterative action generation.…
UniHM: Unified Dexterous Hand Manipulation with Vision Language Model
Zhenhao Zhang, Jiaxin Liu, Ye Shi +1
Planning physically feasible dexterous hand manipulation is a central challenge in robotic manipulation and Embodied AI. Prior work typically relies on object-centric cues or preci…
Learning Semantic Atomic Skills for Multi-Task Robotic Manipulation
Yihang Zhu, Weiqing Wang, Shijie Wu +2
Scaling imitation learning to diverse multi-task robot manipulation remains challenging due to suboptimal demonstrations, behavioral multi-modality, and destructive interference ac…
Commanding Humanoid by Free-form Language: A Large Language Action Model with Unified Motion Vocabulary
Zhirui Liu, Kaiyang Ji, Ke Yang +4
Enabling humanoid robots to follow free-form natural language commands is a critical step toward seamless human-robot interaction and general-purpose embodied AI. However, existing…