10 citations · 13 across the 5 of their papers we have counts for
6 papers
See, Hear, and Feel: Smart Sensory Fusion for Robotic Manipulation
Hao Li, Yizhi Zhang, Junzhe Zhu +7
Humans use all of their senses to accomplish different tasks in everyday activities. In contrast, existing work on robotic manipulation mostly relies on one, or occasionally two mo…
DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness
Changyi Lin, Ziqi Lin, Shaoxiong Wang +1
Vision-based tactile sensors that can measure 3D geometry of the contacting objects are crucial for robots to perform dexterous manipulation tasks. However, the existing sensors ar…
RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
Haochen Shi, Huazhe Xu, Zhiao Huang +2
Modeling and manipulating elasto-plastic objects are essential capabilities for robots to perform complex industrial and household interaction tasks (e.g., stuffing dumplings, roll…
Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning
Zhecheng Yuan, Guozheng Ma, Yao Mu +5
One of the key challenges in visual Reinforcement Learning (RL) is to learn policies that can generalize to unseen environments. Recently, data augmentation techniques aiming at en…
DAIR: Disentangled Attention Intrinsic Regularization for Safe and Efficient Bimanual Manipulation
Minghao Zhang, Pingcheng Jian, Yi Wu +2
We address the problem of safely solving complex bimanual robot manipulation tasks with sparse rewards. Such challenging tasks can be decomposed into sub-tasks that are accomplisha…
PyTouch: A Machine Learning Library for Touch Processing
Mike Lambeta, Huazhe Xu, Jingwei Xu +4
With the increased availability of rich tactile sensors, there is an equally proportional need for open-source and integrated software capable of efficiently and effectively proces…