6 papers
From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation
Yibin Liu, Yaxing Lyu, Daqi Gao +5
Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video MLLMs, trained primarily under a Supervi…
CEI: A Unified Interface for Cross-Embodiment Visuomotor Policy Learning in 3D Space
Tong Wu, Shoujie Li, Junhao Gong +4
Robotic foundation models trained on large-scale manipulation datasets have shown promise in learning generalist policies, but they often overfit to specific viewpoints, robot arms…
AVR: Active Vision-Driven Precise Robot Manipulation with Viewpoint and Focal Length Optimization
Yushan Liu, Shilong Mu, Xintao Chao +7
Robotic manipulation in complex scenes demands precise perception of task-relevant details, yet fixed or suboptimal viewpoints often impair fine-grained perception and induce occlu…
MoiréTac: A Dual-Mode Visuotactile Sensor for Multidimensional Perception Using Moiré Pattern Amplification
Kit-Wa Sou, Junhao Gong, Shoujie Li +4
Visuotactile sensors typically employ sparse marker arrays that limit spatial resolution and lack clear analytical force-to-image relationships. To solve this problem, we present \…
VET: A Visual-Electronic Tactile System for Immersive Human-Machine Interaction
Cong Zhang, Yisheng Yang, Shilong Mu +4
In the pursuit of deeper immersion in human-machine interaction, achieving higher-dimensional tactile input and output on a single interface has become a key research focus. This s…
Exo-ViHa: A Cross-Platform Exoskeleton System with Visual and Haptic Feedback for Efficient Dexterous Skill Learning
Xintao Chao, Shilong Mu, Yushan Liu +4
Imitation learning has emerged as a powerful paradigm for robot skills learning. However, traditional data collection systems for dexterous manipulation face challenges, including…