1 citations · 1 across the 4 of their papers we have counts for
9 papers
TacMan-Turbo: Proactive Tactile Control for Robust and Efficient Articulated Object Manipulation
Zihang Zhao, Zhenghao Qi, Yuyang Li +4
Adept manipulation of articulated objects is essential for robots to operate successfully in human environments. Such manipulation requires both effectiveness--reliable operation d…
Vi-TacMan: Articulated Object Manipulation via Vision and Touch
Leiyao Cui, Zihang Zhao, Sirui Xie +3
Autonomous manipulation of articulated objects remains a fundamental challenge for robots in human environments. Vision-based methods can infer hidden kinematics but can yield impr…
T-800: An 800 Hz Data Glove for Precise Hand Gesture Tracking
Haoyang Luo, Zihang Zhao, Leiyao Cui +5
Human dexterity relies on rapid, sub-second motor adjustments, yet capturing these high-frequency dynamics remains an enduring challenge in biomechanics and robotics. Existing moti…
Simultaneous Tactile-Visual Perception for Learning Multimodal Robot Manipulation
Yuyang Li, Yinghan Chen, Zihang Zhao +4
Robotic manipulation requires both rich multimodal perception and effective learning frameworks to handle complex real-world tasks. See-through-skin (STS) sensors, which combine ta…
Taccel: Scaling Up Vision-based Tactile Robotics via High-performance GPU Simulation
Yuyang Li, Wenxin Du, Chang Yu +6
Tactile sensing is crucial for achieving human-level robotic capabilities in manipulation tasks. As a promising solution, Vision-Based Tactile Sensors (VBTSs) offer high spatial re…
B*: Efficient and Optimal Base Placement for Fixed-Base Manipulators
Zihang Zhao, Leiyao Cui, Sirui Xie +4
B* is a novel optimization framework that addresses a critical challenge in fixed-base manipulator robotics: optimal base placement. Current methods rely on pre-computed kinematics…