25 citations · 66 across the 5 of their papers we have counts for
5 papers
DextAIRity: Deformable Manipulation Can be a Breeze
Zhenjia Xu, Cheng Chi, Benjamin Burchfiel +3
This paper introduces DextAIRity, an approach to manipulate deformable objects using active airflow. In contrast to conventional contact-based quasi-static manipulations, DextAIRit…
Learning 3D Dynamic Scene Representations for Robot Manipulation
Zhenjia Xu, Zhanpeng He, Jiajun Wu +1
3D scene representation for robot manipulation should capture three key object properties: permanency -- objects that become occluded over time continue to exist; amodal completene…
AdaGrasp: Learning an Adaptive Gripper-Aware Grasping Policy
Zhenjia Xu, Beichun Qi, Shubham Agrawal +1
This paper aims to improve robots' versatility and adaptability by allowing them to use a large variety of end-effector tools and quickly adapt to new tools. We propose AdaGrasp, a…
DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactions
Zhenjia Xu, Jiajun Wu, Andy Zeng +2
We study the problem of learning physical object representations for robot manipulation. Understanding object physics is critical for successful object manipulation, but also chall…
Unsupervised Discovery of Parts, Structure, and Dynamics
Zhenjia Xu, Zhijian Liu, Chen Sun +4
Humans easily recognize object parts and their hierarchical structure by watching how they move; they can then predict how each part moves in the future. In this paper, we propose…